DBMS > Cubrid vs. GBase vs. Hazelcast vs. Hypertable vs. IBM Db2 Event Store

System Properties Comparison Cubrid vs. GBase vs. Hazelcast vs. Hypertable vs. IBM Db2 Event Store

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

An analytical database for business intelligence with large customers in China.

A widely adopted in-memory data grid

An open source BigTable implementation based on distributed file systems such as Hadoop

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Relational DBMS

Key-value store

Wide column store

Event Store
Time Series DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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

Score	1.31
Rank	#169	Overall
	#78	Relational DBMS

Score	1.04
Rank	#190	Overall
	#88	Relational DBMS

Score	6.87
Rank	#55	Overall
	#6	Key-value stores

Score	0.23
Rank	#316	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

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

www.gbase.cn

hazelcast.com

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

Technical documentation

cubrid.org/manuals

hazelcast.org/imdg/docs

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

Developer

CUBRID Corporation, CUBRID Foundation

Hazelcast

Hypertable Inc.

IBM

Initial release

2008

2009

2017

Current release

11.0, January 2021

GBase 8a

5.3.6, November 2023

0.9.8.11, March 2016

2.0

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

GNU version 3. Commercial license available

commercial

free developer edition 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

C, C++, Java

Java

C++

C and C++

Server operating systems

Linux
Windows

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Linux, macOS, Windows for the developer addition

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

the object must implement a serialization strategy

Secondary indexes

yes

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

SQL-like query language

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

JCache
JPA
Memcached protocol
RESTful HTTP API

C++ API
Thrift

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

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

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C++
Java
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Event Listeners, Executor Services

yes

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Replicated Map

selectable replication factor on file system level

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

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

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

Role-based access control

fine grained access rights according to SQL-standard

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