DBMS > Datomic vs. IRONdb vs. RocksDB vs. YottaDB

System Properties Comparison Datomic vs. IRONdb vs. RocksDB vs. YottaDB

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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 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)

A fast and solid embedded Key-value store

Primary database model

Relational DBMS

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Score	0.24
Rank	#313	Overall
	#45	Key-value stores

Website

www.datomic.com

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

rocksdb.org

yottadb.com

Technical documentation

docs.datomic.com

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

github.com/facebook/rocksdb/wiki

yottadb.com/resources/documentation

Developer

Cognitect

Circonus LLC.

Facebook, Inc.

YottaDB, LLC

Initial release

2012

2017

2013

2001

Current release

1.0.6735, June 2023

V0.10.20, January 2018

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD

Open Source

AGPL 3.0

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++

C++

Server operating systems

All OS with a Java VM

Linux

Docker
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.

Secondary indexes

yes

SQL

Support of SQL

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

by using the Octo plugin

APIs and other access methods

RESTful HTTP API

HTTP API

C++ API
Java API

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Clojure
Java

.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

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in Lua

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

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

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

Transaction concepts

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

ACID

yes

optimistic locking

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

Users and groups based on OS-security mechanisms

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