DBMS > EventStoreDB vs. Firebird vs. GBase vs. IBM Db2 Event Store

System Properties Comparison EventStoreDB vs. Firebird vs. GBase vs. IBM Db2 Event Store

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Editorial information provided by DB-Engines

Name

Description

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Firebird is an open source RDBMS forked from Borland's InterBase

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

Primary database model

Event Store

Relational DBMS

Event Store
Time Series DBMS

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

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

Website

www.eventstore.com

www.firebirdsql.org

www.gbase.cn

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

Technical documentation

developers.eventstore.com

www.firebirdsql.org/en/reference-manuals

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

Developer

Event Store Limited

Firebird Foundation

General Data Technology Co., Ltd.

IBM

Initial release

2012

2000

As fork of Borland's InterBase

2004

2017

Current release

21.2, February 2021

5.0.0, January 2024

GBase 8a, GBase 8s, GBase 8c

2.0

License

Commercial or Open Source

Open Source

Initial Developer's Public License

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 and C++

C, Java, Python

C and C++

Server operating systems

Linux
Windows

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Linux, macOS, Windows for the developer addition

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

Standard with numerous extensions

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

ADO.NET
C API
JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
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

PSQL

user defined functions

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual 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

Features a multi-generational MVCC architecture, readers do not block writers

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

Users with fine-grained authorization concept

yes

fine grained access rights according to SQL-standard

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