DBMS > Microsoft SQL Server vs. Sphinx

System Properties Comparison Microsoft SQL Server vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Microsofts relational DBMS

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

Primary database model

Relational DBMS

Search engine

Secondary database models

Document store
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Score	1059.72
Rank	#3	Overall
	#3	Relational DBMS

Score	6.54
Rank	#55	Overall
	#6	Search engines

Website

www.microsoft.com/en-us/sql-server

sphinxsearch.com

Technical documentation

docs.microsoft.com/en-ie/sql/sql-server/sql-server-technical-documentation

sphinxsearch.com/docs

Developer

Microsoft

Sphinx Technologies Inc.

Initial release

1989

2001

Current release

SQL Server 2019, November 2019

3.2.1, January 2020

License

Commercial or Open Source

commercial info

restricted free version is available

Open Source info

GPL version 2, commercial licence available

Cloud-based only info

Only available as a cloud service

DBaaS offerings (sponsored links) info

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

XML support info

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Proprietary protocol

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C++

unofficial client library
Java
Perl info

unofficial client library
PHP
Python
Ruby info

unofficial client library

Server-side scripts info

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods info

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

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

Replication methods info

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts info

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys info

Referential integrity

yes

Transaction concepts info

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

ACID

Concurrency info

Support for concurrent manipulation of data

yes

Durability info

Support for making data persistent

yes

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

In-memory capabilities info

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts info

Access control

fine grained access rights according to SQL-standard

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