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What are some commercial and free open-source types of NoSQL databases?

When you want to invest in the commercial databases, you need to make sure that you settle with some of the best in the market. You should have the ability to know the performance and take time to choose the best.

CouchDB – Document Store

Maps keys to data

It provides a RESTful JSON API and is written in Erlang

You can upload functions to index data and then you can call those functions

Has a very simple REST interface

Provides an innovative replication strategy – nodes can reconnect, sync, and reconcile differences after being disconnected for long periods of time

Enables new distributed types of applications and data

MongoDB – Document Store

 

Free-form key-value-like data store with good performance

Powerful, expansive query model

Usability rivals that of Redis

Good for complex data storage needs.

Production-quality sharding capabilities

 

Neo4j – GraphDB

 

Disk-based

Has a restricted, single-threaded model for graph traversal

Has optional layers to expose Neo4j as an RDF store

Can handle graphs of several billion nodes, relationships, or properties on a single machine

Released under a dual license – free for non-commercial use

Apache Hbase – Wide Column Store/Column Families

Built on top of Hadoop, which has functionality similar to Google’s GFS and MapReduce systems

Hadoop’s HDFS provides a mechanism that reliably stores and organizes large amounts of data

Random access performance is on par with MySQL

Has a high performance Thrift gateway

Cascading source and sink modules

 

Redis – Key Value/Tuple Store

 

Provides a rich API and does more operations in memory, using disk only periodically.

It’s extremely fast

Lets you append a value to the end of a list of items that’s already been stored on a key.

Has atomic operations, making it a best-of-breed tally server.

 

Memcached – Key Value/Tuple Store

 

High-performance, distributed memory object caching

Free and open source

Generic and agnostic to the objects/strings it caches

It’s all in-memory data

Simple yet elegant design enables easy development and deployment

Language neutral caching scheme.

Most of the large properties on the web are using it now, except for Microsoft

 

 

Project Voldemort – Eventually Consistent Key Value Store

 

Used by LinkedIn

Handles server failure transparently

Pluggable serialization supports rich keys and values including lists and tuples with named fields

Supports common serialization frameworks including Protocol Buffers, Thrift, and Java Serialization

Data items are versioned

Supports pluggable data placement strategies

Memory caching and the storage system are combined

 

 

Tokyo Cabinet and Tokyo Tyrant – Key Value/Tuple Store

 

Supports hashtable mode, b-tree mode, and table mode

It’s fast and straightforward

Good for small to medium-sized amounts of data that require rapid updating and can be easily modeled in terms of keys and values

 

 

Cassandra – Wide Column Store/Column Families

 

First developed by Facebook

SuperColumns can turnĀ  simple key-value architecture into an architecture that handles sorted lists, based on an index specified by the user.

Can scale from one node to several thousand nodes clustered in different data centers.

Can be tuned for more consistency or availability

Smooth node replacement if one goes down

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