DBMS > GridGain vs. Kingbase vs. openGemini vs. STSdb

System Properties Comparison GridGain vs. Kingbase vs. openGemini vs. STSdb

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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-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

An open source distributed Time Series DBMS with high concurrency, high performance, and high scalability

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	0.01
Rank	#375	Overall
	#39	Time Series DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.gridgain.com

www.kingbase.com.cn

www.opengemini.org
github.com/openGemini

github.com/STSSoft/STSdb4

Technical documentation

www.gridgain.com/docs/index.html

docs.opengemini.org/guide

Developer

GridGain Systems, Inc.

BeiJing KINGBASE Information technologies inc.

Huawei and openGemini community

STS Soft SC

Initial release

2007

1999

2022

2011

Current release

GridGain 8.5.1

V8.0, August 2021

1.1, July 2023

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

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

C and Java

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Integer, Float, Boolean, String

yes

primitive types and user defined types (classes)

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

Standard with numerous extensions

SQL-like query language

APIs and other access methods

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

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP REST

.NET Client API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
Python
Rust

C#
Java

Server-side scripts

Stored procedures

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

user defined functions

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

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

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Administrators and common users accounts

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