David Leeming of the Royal Society of Chemistry discusses how building a platform on MarkLogic has helped his organization deliver content to a non-scientifi...
Dominic Spitz's insight:
David Leeming of the Royal Society of Chemistry discusses how building a platform on MarkLogic has helped his organization deliver content to a non-scientific audience and increase content usage by 30%.
Understand the key challenges faced by enterprises today when delivering search and discovery applications to end users handling Big Data, and, discover how MarkLogic Enterprise NoSQL solutions overcome those challenges.
John O'Donovan, Press Association's Director of Architecture & Development, describes how Press Association used MarkLogic to deliver media content during the 2012 London Olympics, and leverages MarkLogic to develop products for and offer services to its target markets more quickly.
Community Blogs, comments and opinions by industry professionals
Dominic Spitz's insight:
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 do 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.
MarkLogic has delivered a powerful and trusted next-generation Enterprise NoSQL database that enables organizations to turn all data into valuable and actionable information. Organizations around the world rely on MarkLogic’s enterprise-grade technology to make better decisions faster. Key features include ACID transactions, horizontal scaling, real-time indexing, high availability, disaster recovery, government-grade security, and built-in search. MarkLogic has set new standards in scalability, enterprise-readiness, time-to-value, and innovation, giving customers an unmatched competitive edge through game-changing technology.