DBMS > Datomic vs. Firebird vs. H2 vs. HyperSQL vs. Ignite

System Properties Comparison Datomic vs. Firebird vs. H2 vs. HyperSQL vs. Ignite

Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Secondary database models

Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

Technical documentation

docs.datomic.com

www.firebirdsql.org/en/reference-manuals

www.h2database.com/html/main.html

hsqldb.org/web/hsqlDocsFrame.html

apacheignite.readme.io/docs

Developer

Cognitect

Firebird Foundation

Thomas Mueller

Apache Software Foundation

Initial release

2012

2000

As fork of Borland's InterBase

2005

2001

2015

Current release

1.0.6735, June 2023

5.0.0, January 2024

2.2.220, July 2023

2.7.2, June 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

limited edition free

Open Source

Initial Developer's Public License

Open Source

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

Open Source

based on BSD license

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

Java, Clojure

C and C++

Java

C++, Java, .Net

Server operating systems

All OS with a Java VM

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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

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

APIs and other access methods

RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

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

Supported programming languages

Clojure
Java

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

Java

All languages supporting JDBC/ODBC
Java

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

Transaction Functions

PSQL

Java Stored Procedures and User-Defined Functions

Java, SQL

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

Triggers

By using transaction functions

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

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

none

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

Concurrency

Support for concurrent manipulation of data

yes

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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