DBMS > Citus vs. RethinkDB vs. Riak TS vs. Sphinx

System Properties Comparison Citus vs. RethinkDB vs. Riak TS vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Secondary database models

Document store

Spatial DBMS

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

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	2.58
Rank	#105	Overall
	#20	Document stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

www.citusdata.com

rethinkdb.com

sphinxsearch.com

Technical documentation

docs.citusdata.com

rethinkdb.com/docs

www.tiot.jp/riak-docs/riak/ts/latest

sphinxsearch.com/docs

Developer

The Linux Foundation

since July 2017

Open Source, formerly Basho Technologies

Sphinx Technologies Inc.

Initial release

2010

2009

2015

2001

Current release

8.1, December 2018

2.4.1, August 2020

3.0.0, September 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2

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

C++

Erlang

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X

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

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

restricted

yes

full-text index on all search fields

SQL

Support of SQL

yes

standard, with numerous extensions

yes, limited

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP API
Native Erlang Interface

Proprietary protocol

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Erlang

Triggers

yes

Client-side triggers through changefeeds

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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More resources

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