DBMS > Datomic vs. Graph Engine vs. Ingres vs. IRONdb vs. RocksDB

System Properties Comparison Datomic vs. Graph Engine vs. Ingres vs. IRONdb 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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Well established RDBMS

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

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

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Relational DBMS

Time Series 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	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

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

Website

www.datomic.com

www.graphengine.io

www.actian.com/databases/ingres

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

rocksdb.org

Technical documentation

docs.datomic.com

www.graphengine.io/docs/manual

docs.actian.com/ingres

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

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Microsoft

Actian Corporation

Circonus LLC.

Facebook, Inc.

Initial release

2012

2010

1974

originally developed at University Berkely in early 1970s

2017

2013

Current release

1.0.7075, December 2023

11.2, May 2022

V0.10.20, January 2018

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

MIT License

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

.NET and C

C and C++

C++

Server operating systems

All OS with a Java VM

.NET

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

yes

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

APIs and other access methods

RESTful HTTP API

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API

C++ API
Java API

Supported programming languages

Clojure
Java

C#
C++
F#
Visual Basic

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

yes, in Lua

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Automatic, metric affinity per node

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Ingres Replicator

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

fine grained access rights according to SQL-standard

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