DBMS > Cubrid vs. GBase vs. IBM Db2 Event Store vs. SWC-DB vs. Trafodion

System Properties Comparison Cubrid vs. GBase vs. IBM Db2 Event Store vs. SWC-DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

Distributed Event Store optimized for Internet of Things use cases

A high performance, scalable Wide Column DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

www.gbase.cn

www.ibm.com/products/db2-event-store

github.com/kashirin-alex/swc-db
www.swcdb.org

trafodion.apache.org

Technical documentation

cubrid.org/manuals

www.ibm.com/docs/en/db2-event-store

trafodion.apache.org/documentation.html

Developer

CUBRID Corporation, CUBRID Foundation

General Data Technology Co., Ltd.

IBM

Alex Kashirin

Apache Software Foundation, originally developed by HP

Initial release

2008

2004

2017

2020

2014

Current release

11.0, January 2021

GBase 8a, GBase 8s, GBase 8c

2.0

0.5, April 2021

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

Open Source

GPL V3

Open Source

Apache 2.0

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

C, C++, Java

C, Java, Python

C and C++

C++

C++, Java

Server operating systems

Linux
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

yes

schema-free

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

Standard with numerous extensions

yes

through the embedded Spark runtime

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC

Supported programming languages

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

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C++

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

yes

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Active-active shard replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

The vision for Db2
26 February 2019, biplatform.nl

Advancements in streaming data storage, real-time analysis and machine learning
25 July 2019, ibm.com

IBM Builds New Ultra-Fast Platform for Hoovering Up and Analyzing Data from Anywhere
31 May 2018, Data Center Knowledge

How IBM Is Turning Db2 into an 'AI Database'
3 June 2019, Datanami

Best cloud databases of 2022
4 October 2022, ITPro

provided by Google News

2022 All O-Zone Football Team
17 December 2022, Ozarks Sports Zone

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

Share this page