DBMS > Datomic vs. MarkLogic vs. RocksDB vs. SWC-DB

System Properties Comparison Datomic vs. MarkLogic vs. RocksDB vs. SWC-DB

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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

Operational and transactional Enterprise NoSQL database

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

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

Key-value store

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

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

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

www.datomic.com

www.marklogic.com

rocksdb.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.datomic.com

docs.marklogic.com

github.com/facebook/rocksdb/wiki

Developer

Cognitect

MarkLogic Corp.

Facebook, Inc.

Alex Kashirin

Initial release

2012

2001

2013

2020

Current release

1.0.6735, June 2023

11.0, December 2022

8.11.4, April 2024

0.5, April 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

restricted free version is available

Open Source

BSD

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

Schema can be enforced

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

SQL-like query language

APIs and other access methods

RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

C++ API
Java API

Proprietary protocol
Thrift

Supported programming languages

Clojure
Java

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

C++

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

via XQuery or JavaScript

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

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

yes

User concepts

Access control

Role-based access control at the document and subdocument levels

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