DBMS > Cubrid vs. FeatureBase vs. GBase vs. Ignite

System Properties Comparison Cubrid vs. FeatureBase vs. GBase vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Relational DBMS

Key-value store
Relational DBMS

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

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.featurebase.com

www.gbase.cn

ignite.apache.org

Technical documentation

cubrid.org/manuals

docs.featurebase.com

apacheignite.readme.io/docs

Developer

CUBRID Corporation, CUBRID Foundation

Molecula and Pilosa Open Source Contributors

General Data Technology Co., Ltd.

Apache Software Foundation

Initial release

2008

2017

2004

2015

Current release

11.0, January 2021

2022, May 2022

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

C, Java, Python

C++, Java, .Net

Server operating systems

Linux
Windows

Linux
macOS

Linux

Linux
OS X
Solaris
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

yes

SQL queries

Standard with numerous extensions

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

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JDBC
Kafka Connector
ODBC

ADO.NET
C API
JDBC
ODBC

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

Supported programming languages

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

Java
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

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

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes (replicated cache)

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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

fine grained access rights according to SQL-standard

yes

Security Hooks for custom implementations

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