DBMS > GBase vs. H2 vs. IBM Db2 Event Store vs. Quasardb

System Properties Comparison GBase vs. H2 vs. IBM Db2 Event Store vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed Event Store optimized for Internet of Things use cases

Distributed, high-performance timeseries database

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Time Series DBMS

Secondary database models

Spatial DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

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

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.gbase.cn

www.h2database.com

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

quasar.ai

Technical documentation

www.h2database.com/html/main.html

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

doc.quasar.ai/master

Developer

General Data Technology Co., Ltd.

Thomas Mueller

IBM

quasardb

Initial release

2004

2005

2017

2009

Current release

GBase 8a, GBase 8s, GBase 8c

2.2.220, July 2023

2.0

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

free developer edition available

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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, Java, Python

Java

C and C++

C++

Server operating systems

Linux

All OS with a Java VM

Linux

Linux, macOS, Windows for the developer addition

BSD
Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

Standard with numerous extensions

yes

through the embedded Spark runtime

SQL-like query language

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API

Supported programming languages

Java

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

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

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

With clustering: 2 database servers on different computers operate on identical copies of a database

Active-active shard replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

yes, multi-version concurrency control (MVCC)

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

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Cryptographically strong user authentication and audit trail

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