DBMS > GridGain vs. Sequoiadb vs. STSdb vs. VelocityDB

System Properties Comparison GridGain vs. Sequoiadb vs. STSdb vs. VelocityDB

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

NewSQL database with distributed OLTP and SQL

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Document store
Relational DBMS

Key-value store

Graph DBMS
Object oriented DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS
	#21	Object oriented DBMS

Website

www.gridgain.com

www.sequoiadb.com

github.com/STSSoft/STSdb4

velocitydb.com

Technical documentation

www.gridgain.com/docs/index.html

www.sequoiadb.com/en/index.php?m=Files&a=index

velocitydb.com/UserGuide

Developer

GridGain Systems, Inc.

Sequoiadb Ltd.

STS Soft SC

VelocityDB Inc

Initial release

2007

2013

2011

Current release

GridGain 8.5.1

4.0.8, September 2015

7.x

License

Commercial or Open Source

commercial, open source

Open Source

Server: AGPL; Client: Apache V2

Open Source

GPLv2, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, C++, .Net, Python, REST, SQL

C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux

Windows

Any that supports .NET

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes

primitive types and user defined types (classes)

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like query language

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

proprietary protocol using JSON

.NET Client API

.Net

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C++
Java
PHP
Python

C#
Java

.Net

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

JavaScript

Triggers

yes (cache interceptors and events)

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

simple password-based access control

Based on Windows Authentication

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More resources

Recent citations in the news

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