DBMS > MySQL vs. Oracle Rdb vs. SAP SQL Anywhere vs. Sphinx vs. Splice Machine

System Properties Comparison MySQL vs. Oracle Rdb vs. SAP SQL Anywhere vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.54
Rank	#244	Overall
	#114	Relational DBMS

Website

www.mysql.com

www.oracle.com/database/technologies/related/rdb.html

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

sphinxsearch.com

splicemachine.com

Technical documentation

dev.mysql.com/doc

www.oracle.com/database/technologies/related/rdb-doc.html

help.sap.com/docs/SAP_SQL_Anywhere

sphinxsearch.com/docs

splicemachine.com/how-it-works

Developer

Oracle

since 2010, originally MySQL AB, then Sun

Oracle, originally developed by Digital Equipment Corporation (DEC)

SAP

formerly Sybase

Sphinx Technologies Inc.

Splice Machine

Initial release

1995

1984

1992

2001

2014

Current release

9.0.0, July 2024

7.4.1.1, 2021

17, July 2015

3.5.1, February 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

GPL version 2, commercial licence available

Open Source

AGPL 3.0, commercial license 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 and C++

C++

Java

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

HP Open VMS

AIX
HP-UX
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
HTTP API
JDBC
ODBC

Proprietary protocol

JDBC
Native Spark Datasource
ODBC

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

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

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

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

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

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

Database mirroring

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

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

yes

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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