DBMS > Datomic vs. Ehcache vs. IRONdb vs. Kyligence Enterprise vs. RocksDB

System Properties Comparison Datomic vs. Ehcache vs. IRONdb vs. Kyligence Enterprise 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 widely adopted Java cache with tiered storage options

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

A distributed analytics engine for big data, built on top of Apache Kylin

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

Primary database model

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

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

Website

www.datomic.com

www.ehcache.org

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

kyligence.io/kyligence-enterprise

rocksdb.org

Technical documentation

docs.datomic.com

www.ehcache.org/documentation

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

github.com/facebook/rocksdb/wiki

Developer

Cognitect

Terracotta Inc, owned by Software AG

Circonus LLC.

Kyligence, Inc.

Facebook, Inc.

Initial release

2012

2009

2017

2016

2013

Current release

1.0.7075, December 2023

3.10.0, March 2022

V0.10.20, January 2018

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2; commercial licenses available

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

Java

C and C++

Java

C++

Server operating systems

All OS with a Java VM

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.

Secondary indexes

yes

SQL

Support of SQL

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

ANSI SQL for queries (using Apache Calcite)

APIs and other access methods

RESTful HTTP API

JCache

HTTP API

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Clojure
Java

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

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in Lua

Triggers

By using transaction functions

yes

Cache Event Listeners

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

by using Terracotta Server

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

yes

by using Terracotta Server

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate consistency per node, eventual consistency across nodes

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

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

using a tiered cache-storage approach

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

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