DBMS > Datomic vs. RocksDB vs. SiteWhere vs. TerarkDB

System Properties Comparison Datomic vs. RocksDB vs. SiteWhere vs. TerarkDB

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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

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

M2M integration platform for persisting/querying time series data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

www.datomic.com

rocksdb.org

github.com/sitewhere/sitewhere

github.com/bytedance/terarkdb

Technical documentation

docs.datomic.com

github.com/facebook/rocksdb/wiki

sitewhere1.sitewhere.io/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Cognitect

Facebook, Inc.

SiteWhere

ByteDance, originally Terark

Initial release

2012

2013

2010

2016

Current release

1.0.6735, June 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

Open Source

Common Public Attribution License Version 1.0

commercial

restricted open source version available

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

C++

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

RESTful HTTP API

C++ API
Java API

HTTP REST

C++ API
Java API

Supported programming languages

Clojure
Java

C
C++
Go
Java
Perl
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

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

horizontal partitioning

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Users with fine-grained authorization concept

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