DBMS > Datomic vs. Ignite vs. IRONdb vs. OushuDB vs. RocksDB

System Properties Comparison Datomic vs. Ignite vs. IRONdb vs. OushuDB vs. RocksDB

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Key-value store

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.10
Rank	#355	Overall
	#154	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.datomic.com

ignite.apache.org

www.circonus.com/solutions/time-series-database/

www.oushu.com/product/oushuDB

rocksdb.org

Technical documentation

docs.datomic.com

apacheignite.readme.io/docs

docs.circonus.com/irondb/category/getting-started

www.oushu.com/documentation

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Apache Software Foundation

Circonus LLC.

Oushu

Facebook, Inc.

Initial release

2012

2015

2017

2013

Current release

1.0.7075, December 2023

Apache Ignite 2.6

V0.10.20, January 2018

4.0.1, August 2020

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache 2.0

commercial

Open Source

BSD

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++, Java, .Net

C and C++

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

Full-featured ANSI SQL support

APIs and other access methods

RESTful HTTP API

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

HTTP API

JDBC
ODBC

C++ API
Java API

Supported programming languages

Clojure
Java

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

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

yes, in Lua

yes

Triggers

By using transaction functions

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Automatic, metric affinity per node

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes (replicated cache)

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

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

Security Hooks for custom implementations

Kerberos, SSL and role based access

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