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Digital Signal Processing, Data Analytics, Big Data, HPC, Deep Learning, GPGPU, Distributed and Parallel Computing
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Virtual Panel: Current State of NoSQL Databases

NoSQL databases have been around for several years now and have become a choice of data storage for managing semi-structured and unstructured data. These databases offer lot of advantages in terms of linear scalability and better performance for both data writes and reads. InfoQ spoke with four panelists to get different perspectives on the current state of NoSQL databases.
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Pelikan Cache

Pelikan is a framework for building cache services. It is part of Twitter's unified cache project.
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RebornDB: the Next Generation Distributed Key-Value Store - High Scalability -

RebornDB: the Next Generation Distributed Key-Value Store - High Scalability - | EEDSP | Scoop.it

There are many key-value stores in the world and they are widely used in many systems. E.g, we can use a Memcached to store a MySQL query result for later same query, use MongoDB to store documents for better searching, etc.

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Facebook's Memcached Multiget Hole: More machines != More Capacity  - High Scalability -

When you are on the bleeding edge of scale like Facebook is, you run into some interesting problems. As of 2008 Facebook had over 800 memcached servers supplying over 28 terabytes of cache. With those staggering numbers it's a fair bet to think they've seen their share of Dr. House worthy memcached problems.

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In-Memory Database vs. In-Memory Data Grid: Revisited ‹ GridGain

A few months ago, I spoke at the conference where I explained the difference between caching and an in-memory data grid. Today, having realized that many people are also looking to better understand the difference between two major categories in in-memory computing: In-Memory Database and In-Memory Data Grid, I am sharing the succinct version of my thinking on this topic

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Facebook Announces Apollo, a New NoSQL Database for On-line Low Latency Storage

Facebook Announces Apollo, a New NoSQL Database for On-line Low Latency Storage | EEDSP | Scoop.it
Speaking at QCon New York on Wednesday Jeff Johnson, from the core data group at Facebook, announced Apollo, Facebook’s Paxos-like NoSQL database. Written in C++11 on top of the Apache Thrift 2 RPC framework, Apollo is a hierarchical storage system where all the data is split into shards, very much analogous to region servers in HBase.
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RethinkDB 1.13: new protocol and push-pull APIs

RethinkDB 1.13: new protocol and push-pull APIs | EEDSP | Scoop.it
Some interesting changes and new features in RethinkDB 1.13 announced yesterday. Namely:
• replacing the protocol buffers-based protocol for a JSON-protocol
• how does the JSON protocol manage the...
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Grafana - The Graphite dashboard frontend, editor and graph composer

Grafana - The Graphite dashboard frontend, editor and graph composer | EEDSP | Scoop.it
A unique graphite dashboard aimed to be a general purpose dashboard that looks nice and makes it easy to construct and edit dashboards through the UI. It also contains an advanced and unique graph editor and graphite target expression / function editor. Other notible features are fast client side rendering, select to zoom in, multiple y-axes and graph templating.
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CouchDB - short review

CouchDB - short review | EEDSP | Scoop.it
Why using yet another NoSQL? CouchDB was chosen based on requirements and assumptions in the project. Especially, easy multi-master replication seemed to be attractive in the context of the project, which was supposed to be a distributed document database without any relations and rather unstructured data. Unfortunately, as we were going deeper into the project those assumptions turned out not to be 100% correct, and sometimes using this technology was a bit painful.
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Cassandra vs MongoDB vs CouchDB vs Redis vs Riak vs HBase vs Couchbase vs Hypertable vs ElasticSearch vs Accumulo vs VoltDB vs Scalaris comparison :: Software architect Kristof Kovacs

While SQL databases are insanely useful tools, their monopoly in the last decades is coming to an end. And it's just time: I can't even count the things that were forced into relational databases, but never really fitted them. (That being said, relational databases will always be the best for the stuff that has relations.)

But, the differences between NoSQL databases are much bigger than ever was between one SQL database and another. This means that it is a bigger responsibility on software architects to choose the appropriate one for a project right at the beginning.

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NoSQL Data Modeling Techniques

NoSQL Data Modeling Techniques | EEDSP | Scoop.it
NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. This aspect of NoSQL is well-studied both in practice and theory because sp...
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The rise of NoSQL databases

The rise of NoSQL databases | EEDSP | Scoop.it
Although NoSQL database (DB) technology has been around since the 1960s, not until the advent of Web 2.0, when companies such as Google and Amazon began using the technology, did NoSQL’s popularity really take off. The following Google Trends data visualization clearly shows a surge in NoSQL’s popularity beginning around 2010. Indeed, the technology’s longevity and its usefulness within the big data ecosystem make any time a good time to begin your journey with NoSQL. Keep reading for a brief overview of NoSQL that will introduce you to the core features that continue to make this useful technology so popular.
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DZone

DZone | EEDSP | Scoop.it

A presentation from the guys of Redis Labs, focused on four myths:

All In-Memory Databases are Equally FastIn-Memory Computing is Unreliable and InconsistentIn-Memory Computing is Hard to ScaleIn-Memory Computing is Expensive
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Welcome to Mega-KV Homepage!

Welcome to Mega-KV Homepage! | EEDSP | Scoop.it

In-memory key-value stores play a critical role in data processing to provide high throughput and low latency data accesses. In-memory key-value stores have several unique properties that include (1) data intensive operations demanding high memory bandwidth for fast data accesses, (2) high data parallelism and simple computing operations demanding many slim parallel computing units, and (3) a large working set. As data volume continues to increase, our experiments show that conventional and general-purpose multicore systems are increasingly mismatched to the special properties of key-value stores because they do not provide massive data parallelism and high memory bandwidth; the powerful but the limited number of computing cores do not satisfy the demand of the unique data processing task; and the cache hierarchy may not well benefit to the large working set. In this paper, we make a strong case for GPUs to serve as special-purpose devices to greatly accelerate the operations of in-memory key-value stores. Specifically, we present the design and implementation of Mega-KV, a GPU-based in-memory key-value store system that achieves high performance and high throughput. Effectively utilizing the high memory bandwidth and latency hiding capability of GPUs, Mega-KV provides fast data accesses and significantly boosts overall performance. Running on a commodity PC installed with two CPUs and two GPUs, Mega-KV can process up to 160+ million key-value operations per second, which is 1.4-2.8 times as fast as the state-of-the-art key-value store system on a conventional CPU-based platform.

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NoSQL Data Modeling Techniques

NoSQL Data Modeling Techniques | EEDSP | Scoop.it
NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. This aspect of NoSQL is well-studied both in practice and theory because sp...
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In Memory Data Grid Technologies - High Scalability -

In Memory Data Grid Technologies - High Scalability - | EEDSP | Scoop.it
After winning a CSC Leading Edge Forum (LEF) research grant, I (Paul Colmer) wanted to publish ...
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Facebook Apollo NoSQL Database

Facebook Apollo NoSQL Database | EEDSP | Scoop.it

Facebook’s latest project is a NoSQL database called Apollo that provides online low latency hierarchical storage.

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Updated PostgreSQL targets NoSQL market - Big Data Analytics News

Updated PostgreSQL targets NoSQL market - Big Data Analytics News | EEDSP | Scoop.it
Embracing the widely used JSON data-exchange format, the new version of the PostgreSQL open-source database takes aim at the growing NoSQL market of nonrelational data stores, notably the popular MongoDB. The first beta version of PostgreSQL 9.4, released Thursday, includes a number of new features that address the rapidly growing...Read more »
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Small Datum

his has results for a read-only workload where all data is cached. The test query fetches all columns in one doucment/row by PK. For InnoDB all data is in the buffer pool. For TokuMX and MongoDB all data is in the OS filesystem cache and accessed via mmap'd files. The test server has 40 CPU cores with HT enabled and the test clients share the host with mysqld/mongod to reduce variance from network latency. This was similar to a previous test, except the database is in cache and the test host has more CPU cores.

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The NoSQL Family Tree

The NoSQL Family Tree | EEDSP | Scoop.it
Even if it includes just a handful of NoSQL databases, it’s still a nice visualization.
Original title and link: The NoSQL Family Tree (NoSQL database©myNoSQL)
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A few more amps: VoltDB, native memory, and you

This post targets other VoltDB developers who are going to be dealing with the various unconventional ways Volt now uses native memory in the Java portions of the database. It will also be of interest to other Java developers looking to step outside what is typically considered Java's comfort zone for interacting with native memory.

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