DBMS > GridGain vs. OpenTenBase vs. Valentina Server

System Properties Comparison GridGain vs. OpenTenBase vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

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

An enterprise-level distributed HTAP open source database based on PostgreSQL

Object-relational database and reports server

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational 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	0.00
Rank	#385	Overall
	#159	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

www.gridgain.com

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

www.valentina-db.net

Technical documentation

www.gridgain.com/docs/index.html

docs.opentenbase.org
docs.opentenbase.org/en

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

GridGain Systems, Inc.

OpenAtom Foundation, previously Tencent

Paradigma Software

Initial release

2007

1999

Current release

GridGain 8.5.1

2.5, January 2024

5.7.5

License

Commercial or Open Source

commercial, open source

Open Source

BSD-3

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

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

APIs and other access methods

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

ODBC

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
Go
Java
PHP
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

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

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

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10 July 2024, insideBIGDATA

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GridGain in-memory data and generative AI
10 May 2024, Blocks & Files

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8 February 2024, Datanami

provided by Google News

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