DBMS > Microsoft SQL Server vs. Percona Server for MySQL vs. Quasardb vs. Tibero vs. Valentina Server

System Properties Comparison Microsoft SQL Server vs. Percona Server for MySQL vs. Quasardb vs. Tibero vs. Valentina Server

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Enhanced drop-in replacement for MySQL based on XtraDB or TokuDB storage engines with improved performance and additional diagnostic and management features.

Distributed, high-performance timeseries database

A secure RDBMS, designed for easy portability from Oracle

Object-relational database and reports server

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	2.21
Rank	#121	Overall
	#58	Relational DBMS

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Score	0.18
Rank	#329	Overall
	#144	Relational DBMS

Website

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

www.percona.com/software/mysql-database/percona-server

quasar.ai

us.tmaxsoft.com/products/tibero

www.valentina-db.net

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

www.percona.com/downloads/Percona-Server-LATEST

doc.quasar.ai/master

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Microsoft

Percona

quasardb

TmaxSoft

Paradigma Software

Initial release

1989

2008

2009

2003

1999

Current release

SQL Server 2022, November 2022

8.0.36-28, 2024

3.14.1, January 2024

6, April 2015

5.7.5

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

GPL version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

commercial

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++

C and C++

C++

C and Assembler

Server operating systems

Linux
Windows

Linux

BSD
Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

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

yes

Persistent Stored Procedure (PSM)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

consistent hashing

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication
XtraDB Cluster

Source-replica replication with selectable replication factor

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

planned for next version

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

fine grained access rights according to SQL-standard

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