DBMS > MySQL vs. Sequoiadb vs. Sphinx

System Properties Comparison MySQL vs. Sequoiadb vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

NewSQL database with distributed OLTP and SQL

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

Primary database model

Relational DBMS

Key/Value like access via memcached API

Document store
Relational DBMS

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.48
Rank	#260	Overall
	#41	Document stores
	#121	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

www.mysql.com

www.sequoiadb.com

sphinxsearch.com

Technical documentation

dev.mysql.com/doc

www.sequoiadb.com/en/index.php?m=Files&a=index

sphinxsearch.com/docs

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Sequoiadb Ltd.

Sphinx Technologies Inc.

Initial release

1995

2013

2001

Current release

8.3.0, January 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Server: AGPL; Client: Apache V2

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

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Implementation language

C and C++

C++

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

with proprietary extensions

SQL-like query language

SQL-like query language (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

Proprietary protocol

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java
PHP
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

proprietary syntax

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

simple password-based access control

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