NoSQL
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MongoDB
Apache CouchDB: The CouchDB Project
CouchDB provides a RESTful JSON API than can be accessed from any environment that allows HTTP requests. There are myriad third-party client libraries that make this even easier from your programming language of choice. CouchDB’s built in Web administration console speaks directly to the database using HTTP requests issued from your browser. CouchDB is written in Erlang , a robust functional programming language ideal for building concurrent distributed systems. Erlang allows for a flexible design that is easily scalable and readily extensible.
NoSql
Spring Data | SpringSource.org
Spring Projects Spring Data makes it easier to build Spring-powered applications that use new data access technologies such as non-relational databases, map-reduce frameworks, and cloud based data services as well as provide improved support for relational database technologies. Spring Data is an umbrella open source project which contains many subprojects that are specific to a given database. The projects are developed by working together with many of the companies and developers that are behind these exciting technologies. Open Source Development Position : VMware is looking for a highly motivated, team player to work as a software engineer on the Spring Data team working on the open source Spring GemFire project.
Apache Hadoop!
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using a simple programming model. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-avaiability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-availabile service on top of a cluster of computers, each of which may be prone to failures. A wide variety of companies and organizations use Hadoop for both research and production. Users are encouraged to add themselves to the Hadoop PoweredBy wiki page.
Hadoop MapReduce is a programming model and software framework for writing applications that rapidly process vast amounts of data in parallel on large clusters of compute nodes. Hadoop MapReduce is an open source volunteer project under the Apache Software Foundation. We encourage you to learn about the project and contribute your expertise. Here are some starter links:
MapReduce!
Hadoop Distributed File System (HDFS™) is the primary storage system used by Hadoop applications. HDFS creates multiple replicas of data blocks and distributes them on compute nodes throughout a cluster to enable reliable, extremely rapid computations. HDFS is an open source volunteer project under the Apache Software Foundation. We encourage you to learn about the project and contribute your expertise.
HDFS Distributed File System
Use HBase when you need random, realtime read/write access to your Big Data. This project's goal is the hosting of very large tables -- billions of rows X millions of columns -- atop clusters of commodity hardware. HBase is an open-source, distributed, versioned, column-oriented store modeled after Google's Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Hadoop and HDFS.
HBase Home
Understanding HBase and BigTable - Jimbojw.com
From Jimbojw.com The hardest part about learning HBase (the open source implementation of Google's BigTable), is just wrapping your mind around the concept of what it actually is. I find it rather unfortunate that these two great systems contain the words table and base in their names, which tend to cause confusion among RDBMS indoctrinated individuals (like myself). This article aims to describe these distributed data storage systems from a conceptual standpoint.
The Apache Cassandra Project
The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance. Linear scalability and proven fault-tolerance on commodity hardware or cloud infrastructure make it the perfect platform for mission-critical data. Cassandra's support for replicating across multiple datacenters is best-in-class, providing lower latency for your users and the peace of mind of knowing that you can survive regional outages. Cassandra's ColumnFamily data model offers the convenience of column indexes with the performance of log-structured updates, strong support for materialized views , and powerful built-in caching. Cassandra is in use at Netflix , Twitter , Urban Airship , Constant Contact , Reddit , Cisco, OpenX, Digg, CloudKick, Ooyala, and more companies that have large, active data sets. The largest known Cassandra cluster has over 300 TB of data in over 400 machines.