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Twelve competing Dutch newspaper publishers band together to put all their content in one searchable platform called “Newz”

Twelve competing Dutch newspaper publishers band together to put all their content in one searchable platform called “Newz” | MarkLogic - Enterprise NoSQL Database | Scoop.it
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Adam Fowler's curator insight, May 3, 2013 9:00 AM

This is great Newz! *badoomtsch*. Thank you, I'm here all night! #NoSQL

MarkLogic - Enterprise NoSQL Database
Next generation big data, requires a next generation database
Curated by Dominic Spitz
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Big-Data Success Stories: JP Morgan & MarkLogic

Big-Data Success Stories: JP Morgan & MarkLogic | MarkLogic - Enterprise NoSQL Database | Scoop.it

What it does: MarkLogic’s database was designed for unstructured data, like documents, video or any data that doesn’t fit nicely into rows and columns, so customers can build applications without knowing exactly what the data might look like or how they will be formatted.

 

How it’s been used: JPMorgan Chase & Co. uses MarkLogic at the heart of its derivatives processing. Derivatives have more complexity than a ticker symbol and a price, so don’t play well with databases designed for structured data.

Before bringing in MarkLogic, the bank modeled a dozen or so databases—a separate one to serve each of the functions, such as settlement, affirmations, matching and accounting, that it uses the data for. It also had to make the same number of copies of the data to service each database.

 


Via Armando Reis
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Tony Agresta's curator insight, December 17, 2012 8:45 AM

Here are the top uses for MarkLogic in the financial services industry:


Risk Management and Post Trade Processing including

risk aggregation, reference data management and portfolio analysis.

 

Regulatory Compliance for Dodd-Frank Swap Reporting, FATCA Compliance, Know-Your Customer and Anti-Money Laudnering.

 

Customer On Boarding including Institutional Customer Onboarding

and Retail & Private Bank Customer Onboarding

 

Pre-Trade Analytics - Commodity Futures & Historical Tick Data Analysis

 

Customer Insight & Product Targeting in the Credit Card business lines, retail and private banks and corporate finance.

 

Research Management for both broker-dealer research and vendor research

 

Extending this futher into the insruance industry,  Insurance Claims Management for P&C Claims and fraud analysis are both excellent applications for this technology.

Adrian Carr's curator insight, October 2, 2013 9:19 AM

It is hard to believe this is from nearly 2 years ago...Ahead of their time ? maybe.

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MarkLogic - YouTube Channel

MarkLogic - YouTube Channel | MarkLogic - Enterprise NoSQL Database | Scoop.it
Next generation Big Data needs a next generation database. MarkLogic is the trusted platform for Big Data applications designed to drive revenue, streamline ...
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Norwegian Standards Agencies Standardize on MarkLogic® Software

Norwegian Standards Agencies Standardize on MarkLogic® Software | MarkLogic - Enterprise NoSQL Database | Scoop.it

New Content Management and Publishing Solution Streamlines the Adoption and Publishing of up to 2,900 Standards Annually in Norway

Dominic Spitz's insight:

LONDON, May 13, 2014 (BUSINESS WIRE) -- MarkLogic Corporation , the leading Enterprise NoSQL database platform company, today announced that Norway’s three standards agencies - Standards Norway, Norwegian Electrotechnical Committee and Standard Online - have jointly selected MarkLogic 7 to power their content management and publishing platform.

 

Using MarkLogic, the three standards agencies will develop a platform that will allow them to complete the transition to an agile, all-digital delivery model for standards. The goal is to reduce the lead time for publishing new standards from one month to approximately one day.

 

The new platform, which will go live later in 2014, will make it possible for the agencies to offer a broader range of products and services to clients, including customized services for individual clients. This was not previously possible because of the inherent complexity of handling vast tracts of data and the associated business rules. A variety of subscription-based business models will be incorporated to manage these new revenue streams.

With MarkLogic 7, they will be better able to manage the huge volumes of rapidly changing metadata, tables, equations, figures and graphics associated with the localization, adoption and publishing of about 2,900 new national, European and International standards annually in Norway. The result will be a more consistent and efficient standardization process.

 

The three Norwegian standards agencies chose MarkLogic 7 to:

 

Develop a publishing platform for the future that automates the production of PDFs and other formats (e.g., HTML, e-books);

 

Manage content from all editorial workflow systems using a

 

Web-based system featuring a single XML data repository;

 

Handle embedded versioning more efficiently;

 

Deliver fully integrated enterprise search and retrieval for both internal team members and end users;

 

Provide quick and agile application development, enabling rapid

changes to be made to complex big data sets;

 

Build additional revenue streams by offering a wider range of products and services to clients.

 

“We looked at a number of NoSQL vendors but chose MarkLogic because they have a strong heritage in providing database platforms for standards agencies across the world, including ISO ,” said Trine Tveter, Managing Director at Standards Norway. “The new platform will let us improve our productivity, significantly enhance the range of products and services we offer to clients, and monetize these assets more effectively using subscription-based payments. With the new solution we aim to reduce the lead time for publishing a new standard from one month to approximately one day.”

 

MarkLogic 7 is the only schema-agnostic Enterprise NoSQL database that integrates semantics, search and application services with the enterprise features customers require for production applications. Many of the world’s largest publishers are using MarkLogic to transform their businesses. With MarkLogic, organizations can accelerate time to market, optimize data assets and streamline operations, turning data into real revenue.

To learn more about the MarkLogic Enterprise NoSQL database platform and hear from experts on topics such as semantics, elasticity, tiered storage and more, sign up to attend MarkLogic World on May 15th (Amsterdam Arena, Amsterdam), or on May 20th (Emirates Stadium, London). For more information on these free one-day events and to register, please visit world.marklogic.com .

 

About the Norwegian Standards Agencies

Standards Norway handles all standards except those relating to electro-technology and telecoms, while NEK (Norwegian Electrotechnical Committee) is responsible for electro-technical standards. The two organizations jointly own Standard Online, which is responsible for the marketing and sale of standards and related products.

 

About MarkLogic

 

For more than a decade, MarkLogic has delivered a powerful, agile and trusted Enterprise NoSQL database platform that enables organizations to turn all data into valuable and actionable information. Organizations around the world rely on MarkLogic’s enterprise-grade technology to power the new generation of information applications. MarkLogic is headquartered in Silicon Valley with offices in Chicago, Frankfurt, London, New York, Tokyo, Utrecht and Washington D.C. For more information, please visit  www.marklogic.com .

MarkLogic is a registered trademark of MarkLogic Corporation in the United States and/or other countries.
*Other names and brands may be claimed as the property of others.

SOURCE: MarkLogic Corporation

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The Case for Semantic Technology in Financial Services

The Case for Semantic Technology in Financial Services | MarkLogic - Enterprise NoSQL Database | Scoop.it

The Case for Semantic Technology in Financial Services -  Amir Halfon, Financial Services CTO at MarkLogic

Dominic Spitz's insight:

(By Amir Halfon, Financial Services CTO at MarkLogic)

 

In my last post I discussed some of the common use cases of non-relational database technology within our industry. This time I’d like to turn to the use of a specific kind of non-relational technology, namely Semantic Technology.

 

Semantic Technology is specific set of data management tools that aim to provide meaning and context to the data. This is achieved by defining facts about the data, in the form of a Subject-Predicate-Object triple, e.g.: John Smith –> marriedTo –> Jane Doe. These facts can be asserted as they’re discovered, without the need to fit them into any sort of a rigid schema. So, if we later find out that John has a brother named Jim, we can add that fact without the need to have a sibling table in place: John Smith -> brotherOf -> Jim Smith. Furthermore, we can now infer that Jim Smith -> brotherInLawOf -> Jane Dow, and immediately add that piece of information into the database.

 

This is a very brief high level overview, but it should give you a sense of this technology, and the reason many people are excited about it. For the rest of this post I’d like to focus on the use cases that this technology addresses, and the ways its unique features can provide business value around them.

 

Customer 360: You probably guessed from the example above that this might be a use case for semantic technology. The ability to store data about a customer as the data is discovered and ingested from a myriad of diverse sources, without having to go through extended, costly ETL cycles, is a key benefit of this technology. This is especially true when some of this data is non-relational (e.g. onboarding documents, communication records, etc.), and would therefore be quite difficult to stuff into a relational database.

 

Data Provenance: Due to the increased focus on data governance and regulatory compliance in recent years, there’s a growing need to capture the provenance and lineage of data as it goes through its various transformation and changes throughout its lifecycle. Semantic triples provide an excellent mechanism for capturing this information right along with the data it describes. A record representing a trade for instance, can be “decorated” with information about the source of the different elements within it (e.g.: Cash Flow -> wasAttributedTo -> System 123). And this information can be continuously updated as the trade record changes over time, again without the constraints of a schema, which would have made this impossible.

 

Reference Data: Somewhat related to the example above, reference data management can also benefit from semantic technology, by modeling the connections between instruments and legal entities associated with them using triples. Here the richness of semantics as a way to model the real world is key. For instance, modeling the complex relationship between a mortgage backed security and the derivatives built on top of it, or the relationships between legal entities that are affected by M&A activity, can be nightmarish using entity-relational models. Semantic triples represent a much more agile and flexible way to capture facts such as Smith Barney -> acquiredBy -> Morgan Stanley, or CDS_123 -> wasDerivedFrom -> MBS_xyz.

 

The Enterprise Data Management Council has been developing such a semantic model to represent the reference data universe. It’s called the Financial Instruments Business Ontology, and you can find more information about it at www.edmcouncil.org/financialbusiness.

 

Pre-Trade Analytics and Decision Support: Extracting facts from free-form text is an important aspect of providing information to traders and other decision makers, weather the text comes from news feeds, syndicated research articles, tweets, or any other unstructured source. In this case the facts contained in semantic triples represent the context of the unstructured text, e.g.: article123 -> mentions -> Apple Inc. But it can also go further to represent aspects such as the sentiment in the text: article123 -> isBullishOn -> Apple, Inc. This is done using sophisticated tools that can extract facts from the text, so that it can become immediately actionable, without a human first sifting through it.

 

Compliance: Regulatory legal text can be quite difficult to understand, and tracking the policies that would satisfy the regulations can also be an onerous task. Here again, semantic technology and its ability to analyze text and establish relationships within it can provide a huge benefit. The network of rules within the regulatory text, and the policies that satisfy the regulation, can all be represented by a semantic model (e.g. Form W9 ->satisfies -> IRS Requirement xyz). And this model can keep evolving with the policy and regulatory changes,. Thus workflows that are affected by these policies can be automated, alleviating the need to manually check each step. The onboarding process of a new firm for example, is governed by an exorbitant amount of regulations and internal policies that map to them. By using a sematic model to capture these, the onboarding process can be fully automated, and become much more efficient and expedited. This dramatically improves both the customer experience and the cost associated with the onboarding process.

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NoSQL turf war in full swing as MarkLogic lobs grenades at Cloudant, Cloudera and MongoDB.

NoSQL turf war in full swing as MarkLogic lobs grenades at Cloudant, Cloudera and MongoDB. | MarkLogic - Enterprise NoSQL Database | Scoop.it
NoSQL turf war in full swing as MarkLogic lobs grenades at Cloudant, Cloudera and MongoDB
Dominic Spitz's insight:

(...) Bloom is equally dismissive of some of the other NoSQL players currently in the news, questioning their business models and market valuations.

 

"They are raising phenomenal amounts of money, which means they are spending a phenomenal amount of money. Both Cloudera and MongoDB each raised over $50m less than a year before they did their $100m-plus raise. It's a question of what do you do with all that money? Unless they're taking the money from the bankers and turning it into business for customers then it's not a business model.

 

"What generates big news is the amount of money someone's raising. But what that really says is 'we're spending a lot of money, and we're giving up a lot of ownership of the company'. It's not good for the employees and it's not a measure of whether you're a great company or not."

 

He also questioned whether the open-source NoSQL players like MongoDB, which have become firm favourites with developers, can make the leap to heavy-duty enterprise use cases.

 

"MongoDB has been a great lead generation engine for us, because it's helped people understand why they need a different kind of database. You can get productive on it really quickly, but it lacks the enterprise features for them to run their businesses on."

Bloom claimed that as a more established player the MarkLogic integrated solution has had enterprise-level security and ACID transactional capability built in from the start and that others will struggle to emulate this. He also said the firm's more traditional enterprise-focused business model had proved itself in terms of revenues.

 

"MarkLogic makes more revenue than all the other NoSQL players combined," he said. "While the others are working on getting enterprise capability we've moved ahead with tiered storage, semantic search and elastic cloud capabilities."

 

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Reference Data Management - Best with Enterprise NoSQL | MarkLogic

Reference Data Management - Best with Enterprise NoSQL | MarkLogic | MarkLogic - Enterprise NoSQL Database | Scoop.it
Visit MarkLogic.com to read Reference Data Management Best w/ Enterprise NoSQL.
Dominic Spitz's insight:

By Amir Halfon - FS CTO at MarkLogic

 

In an earlier post, I wrote about the differences between NoSQL, what it is, what it isn’t, and some of the misconceptions surrounding it. First I touched on the Operational Trade Store. Now I will focus on enterprise reference data management. While reference data has a very specific meaning in Financial Services – i.e. data about financial instrument and the legal entities associated with them – the term has a broader meaning and relevance to industries at large. And the challenges that financial institutions face are similar for any large organization.


Here’s is a typical situation: numerous M&A activities lead to numerous reference data systems for different lines of business, geographies, etc. This proliferation causes data inconsistencies, which in turn lead to costly processing exceptions. (In the case of investment banks, trade exceptions substantially increase the cost per trade – a key profitability metric.)


In an effort to resolve this challenge, most firms will attempt to consolidate data from these disparate systems into a single “golden copy.” The problem with this approach is the same problem any data consolidation effort faces: It takes such a long time to come up with a “canonical” data model that combines all the sources, and also handles all the data consumers’ requirements, that by the time the modeling exercise is done it is no longer relevant. And so the holy grail of having a single source of truth never comes to fruition.

The alternative? Schema on read. This term refers to loading data directly into the database in its original form , without first creating a common schema – letting the data contain its own structure, then transforming it to any required downstream format in situ, without the need to pre-define a structure that would address all the possible data consumers’ needs as well.


This is the core difference between NoSQL and relational technologies. In fact that’s one of the main reasons NoSQL is gaining so much momentum – the agility that comes from schema-on-read means that changing business needs can be addressed without extensive data modeling exercises and without expensive ETL middleware feeding into them.


And now for the enterprise part: Enterprise reference data is about managing it at an enterprise-wide scale, across lines of business, applications and geographies. Enterprise NoSQL is about accommodating the needs of such enterprise data management, especially in terms security, transactions, availability and scalability.


The need for enterprise-grade security (fine grain, role-based authorizations), availability (HA, DR, etc.) and scalability are fairly self evident, but let’s take a closer look at transactions: Without ACID transactions, a change in a critical legal entity attribute (called a “corporate action” in finance) has to be visible to all systems processing transactions related to this entity at the same exact time; otherwise processes will break (e.g. a confirmation will be send to the wrong party, a trade will fail to clear, etc). And those breakages then have to be fixed using human intervention that carries exorbitant costs.


There are many other examples for where transactions are essential, and the need for full (cross-record) ACID transaction would seem just as obvious as the need for security — if it weren’t for some of the confusion surrounding NoSQL. Much of this confusion resulted from claims that schema flexibility and full transactional consistency were somehow mutually exclusive. Nothing could be further from the truth. It might be hard to implement a schema agnostic, horizontally scaling database that offers ACID transactions across records, but we’ve done it.


I’ve written more about it here: or better yet come to the MarkLogic World conference in April. You’ll hear not only what we at MarkLogic think — but more importantly — what other’s do.

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Linked Data: Best Thing to Happen to Semantic Web | MarkLogic

Linked Data: Best Thing to Happen to Semantic Web | MarkLogic | MarkLogic - Enterprise NoSQL Database | Scoop.it
Visit MarkLogic.com to read Linked Data: Best Thing to Happen to Semantic Web.
Dominic Spitz's insight:

(By Philip Fennell)

 

As a result of the keynote speech at the MarkLogic World 2012 conference I blogged a short piece for O’Reilly entitled “Linked Data Underpins the value of Big Data” where I aired the view that it was the links within, and externally between, datasets that were the real value in Big Data.

 

The increasing interest in Linked Data, and the Semantic Web in general, saw MarkLogic announce, at MarkLogic World 2013, that it was releasing Semantic Web functionality in MarkLogic 7. The 2014 MarkLogic World conference this April will be showcasing how far we are on that path, where we intend to go and how users of MarkLogic are already delivering new applications and services based on these technologies.

 

An interesting question is; how did we get to this point? By that I mean, how did an apparently niche technology, the Semantic Web, which has been in existence for over 14 years, gain such momentum only relatively recently?

 

Well, the underlying technologies of the Semantic Web are the foundation for a web of data, designed as a web-scale technology that utilizes the features that have made the existing web of documents a reality. But, for many years the Semantic Web was seen as a technology looking for a solution. Then, in this context, around 2006/7 the term ‘Linked Data’ was coined and the conversation changed from one of technologies to one of finding solutions to problems:

 

I want to link my data with publically available data to enhance its value.I need to make data integration a much less painful process.I’d like to utilize the relationships (links) between data to learn more about them.I have many disparate data sources that I need to link and query in a consistent and federated way.I need my data to be as agile as my software development processes.If I could publish some of my data openly, so others could link to it, I could attract more customers to my products and services.

These are all problems that organizations have struggled with over the years and there are real solutions to these problems within Linked Data and the Semantic Web.  The Resource Description Framework (RDF) is a data model that is able to respond quickly and easily to change – agile by definition. OWL Ontologies define the rules that govern the interpretation of concepts and relationships that make Linked Data integration a reality. The vast array of publically available datasets can help you enhance the value of your data. The Five Stars of Linked Open Data provide the principles and framework for publishing open data.

 

Since 2007, interest in Linked Data has grown consistently as organizations begin to understand how the Semantic Web technologies can be used to enhance services, enrich products, improve user journeys and streamline internal processes. Join us at MarkLogic World 2014 to discover how you can utilize these technologies to solve real-world problems with MarkLogic. (And if you come a day earlier, we are running a free, day-long, instructor-led course on Using MarkLogic Semantics.)

 

From time to time I will be writing on these pages about the continued evolution of the Semantic Web — and its cohort, Linked Data.

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NoSQL and the Operational Trade Store | MarkLogic

NoSQL and the Operational Trade Store | MarkLogic | MarkLogic - Enterprise NoSQL Database | Scoop.it
Visit MarkLogic.com to read NoSQL and the Operational Trade Store.
Dominic Spitz's insight:

By persisting trade messages as-is, without the need for transforming them into a normalized relational schema. Trade messages contain their own structure, and there’s no need for an over-arching canonical data model in order to process them or report on them.

 

Furthermore, this structure can be modified at the time of querying the data based on the actual usage, rather than trying to create a schema that will handle any foreseeable usage. This is an example of the notion of schema-on-read mentioned in earlier posts.

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MarkLogic’s lead in NoSQL market won’t slow innovation | SiliconANGLE

MarkLogic’s lead in NoSQL market won’t slow innovation | SiliconANGLE | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

The NoSQL market is still relatively new, but the current trends suggest it is on pace to equal or even surpass traditional relational database management systems (RDMS). In this rapidly-emerging market, one company, MarkLogic, is clearly leading the race...

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Organizations Around the World Use MarkLogic For Mission Critical Applications

Organizations Around the World Use MarkLogic For Mission Critical Applications | MarkLogic - Enterprise NoSQL Database | Scoop.it

Our customers seek the flexibility of a NoSQL data model, the reliability of an enterprise-grade database, and the precise search and retrieval capabilities of a best-of-breed search engine. From day one, MarkLogic was built to handle complex, real-time transactional data without risk of data loss.

Dominic Spitz's insight:

Complex systems with complex integrations create complex challenges:

 

Disparate data types

A multitude of schemas

Sparse data

Unstructured data

 

Modeling all of these into a single schema (required by traditional relational databases) would take many, many man years – and in the meantime, more disparate data will have emerged. A new generation database is necessary: one that is schema-agnostic – yet schema aware; that has all the trusted, enterprise capabilities of relational databases – without the limitations.

 

Our customers seek the flexibility of a NoSQL data model, the reliability of an enterprise-grade database, and the precise search and retrieval capabilities of a best-of-breed search engine. From day one, MarkLogic was built to handle complex, real-time transactional data without risk of data loss.

 

We happen to use XML documents as a data model – but make no mistake, we can handle text, data, images, audio, video, application-specific documents, rich file formats, and now even Semantic triples. You can search and query across all these data types – and build immensely complex systems – FAST.

 

MarkLogic clusters on commodity hardware using a shared-nothing architecture and differentiates itself in the market by supporting massive scale and fantastic performance — customer deployments have scaled to hundreds of terabytes of source data while maintaining sub-second query response time.

 

MarkLogic has been in production for over a decade serving mission-critical applications – and has powered:

 

London 2012 Olympics websitesFAA’s Emergency Operations NetworkMission critical systems for 6 of the top 10 of the world’s largest banks8 of top 10 of global information providersMultiple US intelligence agenciesInformatics Corporation of America’s healthcare information exchangesFederally Facilitated Marketplace and the Data Services Hub for the Centers for Medicare  and Medicaid Services

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Availability of MarkLogic 7 on AWS

Availability of MarkLogic 7 on AWS | MarkLogic - Enterprise NoSQL Database | Scoop.it

Industry’s Most Full Featured Enterprise NoSQL Database Platform Available for Cloud Deployments

 

Dominic Spitz's insight:

MarkLogic has announced the availability of MarkLogic 7 on the Amazon Web Services Marketplace.  Enterprises now have full access to the industry’s only schema-agnostic Enterprise NoSQL database that includes search and application services and is engineered to harness the benefits of AWS.

 

MarkLogic 7 on AWS is the same full featured, clustered and elastic product that customers can run on-premise and in cloud environments to run mission-critical applications. This allows companies to set up short-term cloud deployments or adopt a hybrid infrastructure that includes AWS. MarkLogic 7 can span both strategies, easily scaling up or down, without any downtime and with full transactional consistency to ease the migration of applications and workloads between the two infrastructures.

 

MarkLogic placed on the AWS Marketplace

Read the full press release for more details and information.

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MarkLogic - Unified Information Access - Break Down Data Silos

MarkLogic - Unified Information Access - Break Down Data Silos | MarkLogic - Enterprise NoSQL Database | Scoop.it
TDWI (The Data Warehousing Institute) educational institute of business intelligence and data warehousing for executives and professionals worldwide.
Dominic Spitz's insight:

Organizations have important information scattered across silos, some in costly, legacy systems. It's expensive to maintain all those systems, and time-consuming to find the information when it's distributed. Data unification with MarkLogic makes information storage, search, and retrieval easier and faster.

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Gartner Report: Magic Quadrant for Operational Database Management Systems

Gartner Report: Magic Quadrant for Operational Database Management Systems | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

The database market has changed dramatically, and more enterprises are considering and using newer technologies alongside traditional relational databases. In its new Magic Quadrant report, Gartner says:

 

"The operational DBMS market (formerly OLTP) is evolving dramatically, with new, innovative entrants and incumbents supporting the growing use of unstructured data and NoSQL DBMS engines. Information management leaders must understand the market implications affecting DBMS technology decisions."


Get your copy of the Magic Quadrant report for complete insight on where the operational database market is headed in 2013, and which of the newer entrants you should consider for the new generation of information applications.

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Transaction surveillance & compliance monitoring

Transaction surveillance & compliance monitoring | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

Transaction surveillance & compliance monitoring

 

All the data flows pertaining to trading, pricing, and operations can be brought together into a single database that can be configured to provide live, real-time information to the compliance officer and management.

 

With MarkLogic:


• Both real-time and historic data analysis and trending can be seen across all data types.


• External pricing sources (e.g., Trayport / Markit) can all be integrated easily.


• On top of all of the above facilities, email traffic, voice, IM, and all trader activity can be monitored in real time through the same system. Solution

 

Why MarkLogic?

MarkLogic Server is the Enterprise NoSQL database that provides mission-critical data consolidation and analysis solutions to over 350 of the world’s largest companies. It enables them to provide a holistic view of previously siloed data sources and reduce the risk associated with disorganised, disconnected systems.

MarkLogic Server is chosen as the best fit for these organisations because:

• We allow data of all types (structured, semistructured and unstructured) to be loaded and indexed with no prior design effort. This phase alone can typically take 6 to 9 months with traditional database technology.


• We index everything we see in the data, allowing the end user to rapidly create ad hoc and regular reports on all of the disparate data streams.


• We provide sophisticated tools to provide analyses of the underlying data such as facets (unique data values and frequencies), aggregation, co-occurrences, and graphic visualisations.

 

Contact details in the PDF.

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Financial Execs Worry About Data Lineage; Triple Stores Can Calm Fears.

Financial Execs Worry About Data Lineage; Triple Stores Can Calm Fears. | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

The Aite Group, which provides research and consulting services to the international financial services market, spends its fair share of time exploring the data and analytics challenges the industry faces. Senior analyst Virginie O’Shea commented on many of them during a webinar this week sponsored by enterprise NoSQL vendor MarkLogic.

 

Dealing with multiple data feeds from a variety of systems; feeding information to hundreds of end users with different priorities about what they need to see and how they need to see it; a lack of a common internal taxonomy across the organization that would enable a single identifier for particular data items; the toll ETL, cleansing, and reconciliation can take on agile data delivery; the limitations in cross-referencing and linking instruments and data to other data that exact a price on data governance and quality – they all factor into the picture she sketched out.

 

Things aren’t going to get any easier, either, both as electronic data and regulatory requirements around financials data increases in Europe and the States. “We are looking at much more data to get a handle around, and as part of shadow bank regulations we’ll see more data reporting in particular areas,” she said. “The profile of data management is being raised but it’s proving challenging.”

In addition to improving processes around data aggregation, and being better able to slice and dice that data as necessary, the basic accuracy and reliability of data is a concern. Among the issues that financial services data management executives are worrying about, she noted, is data lineage. Being able to pinpoint the source of data and its path through systems can help with audit trails that will enable risk managers to know they are making the right decisions based on the right data, as well as help meet regulatory requirements.

 

In fact, financial services firms may be able to lower risk management demands if they can prove they have a better handle on their own data with more accurate risk calculations.

 

The MarkLogic NoSQL document database has capabilities that can help with such challenges, according to Amir Halfon, MarkLogic CTO, Financial Services, who participated in the webinar. “Those familiar with RDF and some other semantic standards, we now support those as well, so you can look at it as a cross between a document store and a semantic triple store,” he said. “In fact, this is one way that data lineage and provenance can be supported.” Triple stores help users to connect the dots of data lineage and data journeys with joins across relationships on objects – where the data comes from, who was the last person to touch it, and what was the latest transformation it went through, for example.

 

Halfon also noted that triples can be added easily as data is ingested.  “That is one way to handle data provenance – as part of ingestion as well as when data changes through the system,” he said.

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MarkLogic: Battling for pole position in the NoSQL market

MarkLogic: Battling for pole position in the NoSQL market | MarkLogic - Enterprise NoSQL Database | Scoop.it
MarkLogic CEO Gary Bloom talks to Diginomica about size, enterprise-level table stakes and the lead generation engine provided by his open source database rivals.
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MarkLogic announces support for JavaScript, JSON by improving enterprise NoSQL Database Platform

MarkLogic announces support for JavaScript, JSON by improving enterprise NoSQL Database Platform | MarkLogic - Enterprise NoSQL Database | Scoop.it
MarkLogic announces support for JavaScript, JSON by improving enterprise NoSQL Database Platform

Via Adrian Carr
Dominic Spitz's insight:

(by Adrian Carr, EMEA VP)

 

Big announcements at MarkLogic World this week.  

Support for server-side JavaScript will dramatically increase accessibility.

The real news is somewhat larger.

Customers asked for Semantic/Triple Store capabilities - these were delivered in November

Customers asked for a free developer license and lower entry cost production licenses for smaller organisations - these were both delivered in November too.

Customers have asked for native JSON and server-side JavaScript to broaden the developer pool they can draw from - to be delivered in the next version.

Is your software supplier listening to your needs ?

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Adrian Carr's curator insight, April 9, 1:21 PM

Big announcements at MarkLogic World this week.  

Support for server-side JavaScript will dramatically increase accessibility.

The real news is somewhat larger.

Customers asked for Semantic/Triple Store capabilities - these were delivered in November

Customers asked for a free developer license and lower entry cost production licenses for smaller organisations - these were both delivered in November too.

Customers have asked for native JSON and server-side JavaScript to broaden the developer pool they can draw from - to be delivered in the next version.

Is your software supplier listening to your needs ?

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NoSQL Vendor MarkLogic Announces Record Year!!

NoSQL Vendor MarkLogic Announces Record Year!! | MarkLogic - Enterprise NoSQL Database | Scoop.it

“We continue to improve and enhance our platform with new enterprise features and search capabilities to further differentiate ourselves from the competition and provide customers with the industry’s best Enterprise NoSQL database platform for solving the most complex data integration challenges,” said Gary Bloom, CEO of MarkLogic.

Dominic Spitz's insight:

MarkLogic, the US-based developer of NoSQL database software, has announced its most profitable year to date, although the private company didn’t offer any numbers.

 

It has attributed the results to strong growth in European and Asia Pacific markets, and the release of MarkLogic 7 – its latest database platform which features data store elasticity, tiered storage and semantics capabilities.

 

“We continue to improve and enhance our platform with new enterprise features and search capabilities to further differentiate ourselves from the competition and provide customers with the industry’s best Enterprise NoSQL database platform for solving the most complex data integration challenges,” said Gary Bloom, CEO of MarkLogic.

 

Riding the wave

 

MarkLogic was founded in 2001 to address the emergence of XML as a document markup standard and XQuery as the means for accessing large collections of documents. Over time, the company evolved to take advantage of the emerging NoSQL movement, with a product that combines a database, search engine and application services together in one platform.

 

MarkLogic customers include the BBC, Associated Press, LexisNexis, Warner Bros. and the Royal Society of Chemistry.

 

During the year ending with 31 January, the company launched MarkLogic 7 – its most powerful and feature-rich enterprise platform. It also introduced new pricing and packaging, a free developer license and cloud-ready hourly pricing for Amazon Web Services.

 

To finance these changes, in April 2013 MarkLogic raised $25 million in venture capital. The investment paid off, in the shape of record license revenues.

 

“The market is awakening to what NoSQL is,” Adrian Carr, VP of EMEA at MarkLogic, told TechWeek. “Two years ago, when we met a customer, we had to explain what NoSQL was, and once we breached that gap, we had to look for use cases. Only then would they start to evaluate different vendors. Today, this cycle is compressing, and soon we’ll get to a point where people in the market already know that NoSQL is the answer to their data problems, and they just have to pick the right vendor depending on their challenges.”

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How can one guarantee cross-record ACID transactions in a horizontally-scalable, schema-agnostic database?

How can one guarantee cross-record ACID transactions in a horizontally-scalable, schema-agnostic database? | MarkLogic - Enterprise NoSQL Database | Scoop.it

The short answer is an architectural pattern called Multi Version Concurrency Control or MVCC.

Dominic Spitz's insight:

By Amir Halfon - MarkLogic FS CTO

 

My last post talked about Enterprise NoSQL and ACID vs. BASE in the context of handling data variety. In this one I'd like to delve deeper into transactional, Enterprise NoSQL. 

 

Let's start by focusing on the main question: How can one guarantee cross-record ACID transactions in a horizontally-scalable, schema-agnostic database?

 

The short answer is an architectural pattern called Multi Version Concurrency Control or MVCC.

 

The basic notion behind MVCC is that records are never modified, but instead a new version is created every time a record changes. The system eventually deletes these old versions after a configureable period of time, but within that time window it's simple to roll back a transaction. More over, it's also straight forward to roll back the entire database to an earlier point in time - A.K.A. point-in-time recovery - a key requirement of enterprise databases. 

 

Interestingly enough, the availability of Enterprise NoSQL - a schema-agnostic technology that satisfies these requirements - is now starting to blur the boundaries between the traditional Data Warehouse, Operational Data Store and DataMart, and converge them into a single store. The enabler for this is the notion of schema-on-read (vs. the traditional schema-on-write), which refers to the ability to enter data without requiring a pre-defined schema, while supporting multiple schemas when the data is read. This means that the categories mentioned above can be merged into a single platform that satisfies many data consumers without requiring intense modeling and transformation ahead of time.

 

In addition to schema-on-read, it is also the unification of data management and search that is key to handling data diversity. In fact it was the immense success of search engines that paved the way to this new data management paradigm. Search technologies have established the use of a rich set of indexes as a means for querying non-relational data. From there it was a small leap to apply this notion to a database, converging it with database indexing. But unlike traditional RDBMS, indexes in the NoSQL world do not have to be pre-defined, nor rebuilt as the data changes.

 

So we're witnessing some related convergence trends - the convergence of structured and unstructured data, that of database and search technologies, and of traditional data management tiers into a single platform.

 

My next post will tie these concepts back to the related industry use-cases that benefit from them.

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Datawatch and MarkLogic Announce a Global Strategic Alliance to Deliver Next Generation Visualization Solutions for Big Data Environments - WSJ.com

Datawatch and MarkLogic Announce a Global Strategic Alliance to Deliver Next Generation Visualization Solutions for Big Data Environments - WSJ.com | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

Datawatch Corporation (NASDAQ-CM: DWCH), a leading provider of visual data discovery solutions, today announced a new global strategic alliance with MarkLogic Corporation, the leading Enterprise NoSQL database platform. The combination of technologies created by this partnership for the first time enables the value of all enterprise data--including streaming real-time sources--to be exploited. With it, organizations can store, access and visualize massive amounts of data, from any source and in any format, in order to make better informed business decisions and create scalable, new generation applications to drive revenue, streamline operations, and mitigate risk.

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MARKLOGIC WORLD TOUR 2014 (Amsterdam & London in EMEA)

MARKLOGIC WORLD TOUR 2014 (Amsterdam & London in EMEA) | MarkLogic - Enterprise NoSQL Database | Scoop.it
MARKLOGIC WORLD TOUR 2014 MarkLogic World brings together experts in the database world. Join us in the city of your choice, to meet with experts, attend sessions covering Semantics, Elasticity, Tiered Storage & more.
Dominic Spitz's insight:
MarkLogic World is getting a makeover in 2014!

Instead of one event, we’re bringing the show on the road! MarkLogic World 2014 will kick off with a technical, jam-packed 2-day paid conference in San Francisco, focused on training & educating our customers and partners. Network with other MarkLogic experts, share best practices, get hands-on expertise with our pre-conference training courses, and leverage valuable one-on-one time with the technologists who build our award-winning products.

 

Following our in-depth 2-day event, we’re bringing MarkLogic World to you in May and June, 2014. The MarkLogic World Tour will hit several cities in Europe and the US for a one-day complimentary conference, with 2 tracks – one focused on our existing customers (slightly technical) and a second focused on those new to MarkLogic (business level).

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Tame Unruly Data - MarkLogic

Tame Unruly Data - MarkLogic | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

Information is meant to be searched, studied, and shared.
Why are so many companies still struggling to reign in various data sources, and missing out on opportunities?

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Tableau and Marklogic Visualize Unstructured Data

Tableau and Marklogic Visualize Unstructured Data | MarkLogic - Enterprise NoSQL Database | Scoop.it
One of the most important features for managing unstructured data is the ability to quickly search the data and get back relevant results. Marklogic provides support for full text searches as well as complex searches on Unstructured data.
Dominic Spitz's insight:

Everyone talks about extracting value from big data and specifically tapping into the value of unstructured data. Marklogic, a Tableau partner, is actually helping customers do it! Marklogic’s goal is to help customers rapidly make sense of large amounts of unstructured data. Marklogic is the leading Enterprise NoSQL database on the market due to how quickly they can process, catalog, store and search tons of unstructured data. This data can then be exposed to Tableau users through the “Other ODBC” connection in Tableau.

 

One of the most important features for managing unstructured data is the ability to quickly search the data and get back relevant results. Marklogic provides support for full text searches as well as complex searches on Unstructured data. Tableau customers can initiate these searches using simple parameters in Custom SQL. Marklogic then searches the entire indexed document, not just titles of documents or the metadata.

 

After searching the unstructured data you may want to enrich that data with outside relevant information. Marklogic utilizes a triple store and the semantic web to provide customized data that enriches the data discovery process.

 

To demonstrate Tableau and Marklogic searching and visualizing unstructured data, we created a sample workbook of indexed public mailing list messages. This workbook is a subset of emails from Markmail.org. You can see the dashboard here on Tableau Public.

You can start with the search bar created using a Tableau parameter in custom SQL. That parameter is just the right hand side of a SQL MATCH query, and it can be anything you’d expect from a powerful search engine like MarkLogic: Booleans, proximity search, fielded search and so on. The entire email is searched, not just a column like you’d get with a relational database! Try it! Search for any term and click on an email snippet. You will see a new window appear showing the entire document (in this case an email).

 

If you type in “Hadoop” with a capital H (Marklogic search uses SPARQL which is case sensitive), you will see the right hand side of the dashboard fill with new data. This isn’t just any data. It’s not in a database per se, it’s coming from the Web. MarkLogic’s triple store indexes to see “what else do we know?” — like an infobox you see sometimes with Google searches.

 

(A note about this dashboard. In order to provide this demo to Tableau Public, we have extracted the data from MarkLogic into a TDE file — but you could easily run live data from MarkLogic into Tableau for real-time analysis on your own server.)

For more information on Tableau and Marklogic, you can view a recent webinar on Analytics, NoSQL, and Visualization hosted by Marklogic and Tableau.

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Big Data Technology at the Royal Society of Chemistry

Big Data Technology at the Royal Society of Chemistry | MarkLogic - Enterprise NoSQL Database | Scoop.it
MarkLogic's enterprise NoSQL platform allows science publisher to reach out to new audiences and platforms, says strategist
Dominic Spitz's insight:

The RSC was founded in 1841, its clients and contributors consisted of a small group of gentleman scientists, mostly based in London. Today its materials are used by millions all around the world - researchers, universities, institutions, R&D departments - just last week the organisation added its millionth global user of the educational platform for secondary school students and teachers Learn Chemistry.

 

RSC needed to digitize the Society's vast leather-bound archive, employing a third-party bureau to convert 1.4 million pages of written word and chemical formulae into SGML and XML, a project that was completed in 2004. From there a simple website was created with pages hosted as PDF files. Then came the task of making the archive searchable. 

 

According to David Leeming, strategic innovation group solutions manager at the Royal Society of Chemistry, "We wanted to get more out of the XML we'd been collecting. It seemed obvious it wasn't going to fit into a relational model," Leeming told Computing. "We wanted to deliver all that information back to 1841 but also expand and develop new products and services. We wanted to get more out of the discovery process and make sure it was available in different formats."

To make this data searchable and to create a publishing platform that would enable new products and services to be rolled out quickly, RSC partnered with  MarkLogic.  Please read the complete story here to learn how MarkLogic helped RSC solve their data challenges. 

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MarkLogic Rolls Out the Red Carpet for Semantic Triples

MarkLogic Rolls Out the Red Carpet for Semantic Triples | MarkLogic - Enterprise NoSQL Database | Scoop.it
Dominic Spitz's insight:

The capability to store and search semantic triples in MarkLogic 7 is one of the most compelling new features of the new NoSQL database. The concept of semantic triples is central to the Resource Description Framework (RDF) way of storing and searching for information. Instead of relating information in a database using an "entity-relationship" or "class diagram" model, the RDF framework enables links between pieces of data to be searched using the "subject-predicate-object" concept, which more closely corresponds to the way humans think and communicate.

 

The real power of this approach becomes evident when one considers the hugely disparate nature of information on the Internet. An RDF powered application can build links between different pieces of data, and effectively "learn" from the connections created by the semantic triples. This is the big (and as yet unrealized) pipe dream of the semantic Web.

 

RDF has been around for a while, and while you probably wouldn't call it mainstream, there are a handful of applications using this approach. What makes MarkLogic's approach unique is that it's storing the semantic triples--the linked data--right inside the main NoSQL database, where it can make use of all the rich data and metadata stored in documents and other semi-structured files that NoSQL databases like MarkLogic are so good at storing.

 

This approach puts semantic triples right where it can do the most good. "Until now there has been a disconnect between the incredible potential of semantics and the value organizations have been able to realize," states MarkLogic's senior vice president of product strategy, Joe Pasqua.

 

"Managing triples in dedicated triple stores allowed people to see connections, but the original source of that data was disconnected, ironically losing context," he continues. "By combining triples with a document store that also has built-in querying and APIs for delivery, organizations gain the insights of triples while connecting the data to end users who can search documents with the context of all the facts at their fingertips."

 

MarkLogic says early adopters of MarkLogic 7 have already started playing around with the new semantic features, which uses the SPARQL query language to interrogate or infer the relationships in semantic triples. This includes the databases that powered websites created for the 2012 Summer Olympics; financial services firms that use semantic triples to manage data and risk; law enforcement organizations that use semantic triples to identify crime or fraud patterns; drug companies that use the technology to infer risk and decide which drugs to take to trial; and procurement agents, who use it to rationalized purchasing decisions.

 

"The semantic features we're putting into MarkLogic have gotten a lot of interest from our user base, and even our prospect base," MarkLogic CMO Michaline Todd told Datanami last month. "The capability to use MarkLogic as your RDF Triple Store and to use open link data helps customers to build more powerful, very textually relevant applications that deliver the exact information people need as they need it."

 

Dave Schubmehl, an IDC research director in the field of search and content analytics, says the new capabilities give MarkLogic an advantage over other NoSQL database vendors, and even over traditional relational database (RDB) vendors. "While other database vendors offer limited semantic/RDF support, the combination of full XML support with robust semantic and RDF functionality and performance really makes MarkLogic a significant contender for semantic based applications and solutions," he says via email.

Schubmehl says he sees semantic applications growing significantly. "Traditional search systems look at the 'who,' 'what,' 'when,' and 'where' in unstructured information. Government, publishers, financial services firms, and many other types of organizations are all looking to utilize semantic technologies to answer the 'why,' and this can only be done by finding and understanding the relationships between concepts, phrases, and keywords. This is what RDF and semantic capabilities can provide."

 

MarkLogic 7 brings several other notable new features, including a new tiered storage mechanism. This gives customers the capability to use Hadoop File System (HDFS) as a storage mechanism, as well as the capability to deploy a single NoSQL database across multiple, heterogeneous, and geographically disparate platforms, including Amazon S3 and EBS.

The HDFS integration gives MarkLogic customers several configuration options. They can run the database on HDFS as a shared file system, use HDFS as a storage tier, or even use HDFS in a mixed workload scenario that combines MapReduce batch processing and real-time processing on NoSQL.

 

MarkLogic is one of a group of NoSQL database vendors that are trying to disrupt the market for production database systems, which for so long as been dominated by RDB vendors, like Oracle, IBM, and Microsoft. Whereas Hadoop and related tools are primarily being used for batch-oriented analytic workloads, MarkLogic and other NoSQL database vendors see themselves driving production business systems that have traditionally been powered by the RDBs.

"At many of our customers, we are the primary application," Aaron Rosenbaum, MarkLogic's director of product management, told Datanami last month. "At many customers, we're the majority of the revenue they're driving in their organization. These are almost exclusively custom applications."

 

MarkLogic 7, along with the tiered storage and semantics options, are available now through the company's early access program, and are expected to become generally available in late November.

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MarkLogic 7: Tame Big Data Using Semantics

MarkLogic 7:  Tame Big Data Using Semantics | MarkLogic - Enterprise NoSQL Database | Scoop.it
Visit MarkLogic.com to read MarkLogic Semantics.
Dominic Spitz's insight:

Organizations are finding they can make better-informed decisions, reduce risk, and convey more accurate information by combining documents, data, and now RDF triples (also known as Linked Data) in one flexible architecture - The MarkLogic Enterprise NoSQL Database. Read more by clicking the link.

 

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