DBMS > Axibase vs. GridDB vs. openGauss vs. Valentina Server

System Properties Comparison Axibase vs. GridDB vs. openGauss vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Scalable in-memory time series database optimized for IoT and Big Data

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Object-relational database and reports server

Primary database model

Time Series DBMS

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

Document store
Spatial DBMS

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

Score	0.21
Rank	#308	Overall
	#25	Time Series DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

axibase.com/docs/atsd/finance

griddb.net

gitee.com/opengauss
opengauss.org

www.valentina-db.net

Technical documentation

docs.griddb.net

docs.opengauss.org/en
gitee.com/opengauss/docs

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

Developer

Axibase Corporation

Toshiba Corporation

Huawei and openGauss community

Paradigma Software

Initial release

2013

2019

1999

Current release

15585

5.1, August 2022

3.0, March 2022

5.7.5

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

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++

C, C++, Java

Server operating systems

Linux

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

numerical, string, blob, geometry, boolean, timestamp

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL92, SQL-like TQL (Toshiba Query Language)

ANSI SQL 2011

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC

ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

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

C
C++
Java

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

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID at container level

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

Access rights for users can be defined per database

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

fine grained access rights according to SQL-standard

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