DBMS > Datomic vs. RethinkDB vs. RocksDB vs. SAP SQL Anywhere vs. Sphinx

System Properties Comparison Datomic vs. RethinkDB vs. RocksDB vs. SAP SQL Anywhere vs. Sphinx

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

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

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.datomic.com

rethinkdb.com

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

sphinxsearch.com

Technical documentation

docs.datomic.com

rethinkdb.com/docs

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

Developer

Cognitect

The Linux Foundation

since July 2017

Facebook, Inc.

SAP

formerly Sybase

Sphinx Technologies Inc.

Initial release

2012

2009

2013

1992

2001

Current release

1.0.6735, June 2023

2.4.1, August 2020

8.11.4, April 2024

17, July 2015

3.5.1, February 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

Apache Version 2

Open Source

BSD

commercial

Open Source

GPL version 2, commercial licence 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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

Supported programming languages

Clojure
Java

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Go
Java
Perl
Python
Ruby

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Transaction Functions

yes, in C/C++, Java, .Net or Perl

Triggers

By using transaction functions

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

range based

horizontal partitioning

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

yes

Source-replica replication

Database mirroring

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

yes

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

yes

The original contents of fields are not stored in the Sphinx index.

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

yes

users and table-level permissions

fine grained access rights according to SQL-standard

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