MongoDB (from "humongous") is a scalable, high-performance, open source, dynamic-schema, document-oriented database. MongoDB bridges the gap between key-value stores (which are fast and highly scalable) and traditional RDBMS systems. MongoDB runs well on Amazon EC2. MongoDB uses BSON as the data storage and network transfer format for "documents". BSON is a binary encoded serialization of JSON-like documents. MongoDB could be accessed from programming language C, C++, Java, PHP, Python and Ruby. 
 It supports: 
 <UL>
	<LI>DBA operations from the shell</LI>
	<LI>Sharding</LI>
	<LI>Replication</LI>
	<LI>Security</LI>
	<LI>Backup</LI>
	<LI>Database Profiler</LI>
	<LI>Full Text Search</LI> 
 </UL>

MongoDB (from "humongous") is a scalable, high-performance, open source, dynamic-schema, document-oriented database. MongoDB bridges the gap between key-value stores (which are fast and highly scalable) and traditional RDBMS systems.

MongoDB - NoSQL Document Store Database

Crate is an open source, highly scalable, shared-nothing distributed SQL database. Crate offers the scalability and performance of a modern No-SQL database with the power of Standard SQL. Crate’s distributed SQL query engine lets you use the same syntax that already exists in your applications or integrations, and have queries seamlessly executed across the crate cluster, including any aggregations, if needed.

Crate - The fast, scalable, easy to use SQL database with native full text search

H2 database is very fast, open source database engine. 
 It supports : 
 <UL>
	<LI>It supports SQL and JDBC standards</LI>
	<LI>Encrypted database</LI> 
	<LI>Security and Authentication</LI>
	<LI>Multiple index types (b-tree, tree, hash)</LI> 
	<LI>Contains a recovery tool that can dump the contents of the database</LI> 
	<LI>Clustering</LI>
	<LI>Full text search</LI>
	<LI>Temporary Tables</LI> 
	<LI>User-Defined Datatypes</LI>
 </UL>

H2 database is very fast, open source database engine. It supports SQL and JDBC standards. It can run in Embedded and Server mode and it has clustering support.  


H2 Database - Java based Database Engine

RadonDB is a cloud-native database based on MySQL. It’s architected to fully distributed cluster that delivering unlimited scalability (scale-out), capacity and performance. It supports distributed transaction capability for high data consistency, and leverage MySQL as storage engine with trusted data reliability. RadonDB is compatible with MySQL protocol, at mean time supports automatic table sharding, that simplifying the maintenance and operation workflow.
 
Its features include Automatic Table Sharding, Distributed Transaction, Distributed Joins, Distributed Full Text Search, Parallel Execution, Connection Thread Pool, Auditing and Logging and lot more.

RadonDB is a cloud-native database based on MySQL. It’s architected to fully distributed cluster that delivering unlimited scalability (scale-out), capacity and performance. It supports distributed transaction capability for high data consistency, and leverage MySQL as storage engine with trusted data reliability. RadonDB is compatible with MySQL protocol, at mean time supports automatic table sharding, that simplifying the maintenance and operation workflow.

RadonDB  - Cloud-native MySQL database for building global, scalable cloud services

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in <A HREF="http://www.linkedin.com/signal/" target="_blank">LinkedIn Signal</A> and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and well-formed and structured metadata. 
 It supports Fast realtime updates, Complex query language and REST/JSON api, Hadoop integration and lot more.

Sensei is a distributed data system that was built to support many product initiatives at LinkedIn, including the real-time faceted search in LinkedIn Signal and the news feed and tabs on the Homepage. Sensei is both a search engine and a database. It is designed to query and navigate through documents that consist of unstructured text and  well-formed and structured metadata. Sensei is both a search engine and a database.

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

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MongoDB - NoSQL Document Store Database

Crate - The fast, scalable, easy to use SQL database with native full text search

H2 Database - Java based Database Engine

RadonDB - Cloud-native MySQL database for building global, scalable cloud services

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

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MongoDB - NoSQL Document Store Database

Crate - The fast, scalable, easy to use SQL database with native full text search

H2 Database - Java based Database Engine

RadonDB - Cloud-native MySQL database for building global, scalable cloud services

SenseiDB - Distributed, Realtime, Semi-Structured Database from LinkedIn

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