DBMS > Altibase vs. Microsoft Azure SQL Database vs. MySQL vs. ScyllaDB vs. Sphinx

System Properties Comparison Altibase vs. Microsoft Azure SQL Database vs. MySQL vs. ScyllaDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

Widely used open source RDBMS

Cassandra and DynamoDB compatible wide column store

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

Wide column store

Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Key-value store

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

altibase.com

azure.microsoft.com/en-us/products/azure-sql/database

www.mysql.com

www.scylladb.com

sphinxsearch.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.microsoft.com/en-us/azure/azure-sql

dev.mysql.com/doc

docs.scylladb.com

sphinxsearch.com/docs

Developer

Altibase

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

ScyllaDB

Sphinx Technologies Inc.

Initial release

1999

2010

1995

2015

2001

Current release

v7.3, 2023, August 2023

V12

8.4.0, April 2024

ScyllaDB Open Source 5.4.1, January 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Open Source (AGPL), commercial license available

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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Implementation language

C++

C and C++

C++

Server operating systems

AIX
HP-UX
Linux

hosted

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

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

cluster global secondary indices

yes

full-text index on all search fields

SQL

Support of SQL

ANSI SQL-92

yes

with proprietary extensions

SQL-like DML and DDL statements (CQL)

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC
Proprietary protocol

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

Proprietary protocol

Supported programming languages

C
C++
Java

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

stored procedures and stored functions

Transact SQL

yes

proprietary syntax

yes, Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

yes, with always 3 replicas available

Multi-source replication
Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

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
Tunable Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

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

in-memory tables

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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