DBMS > Microsoft SQL Server vs. MonetDB vs. mSQL vs. Splunk vs. TimescaleDB

System Properties Comparison Microsoft SQL Server vs. MonetDB vs. mSQL vs. Splunk vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

mSQL (Mini SQL) is a simple and lightweight RDBMS

Analytics Platform for Big Data

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Relational DBMS

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Trend Chart

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

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

www.monetdb.org

hughestech.com.au/products/msql

www.splunk.com

www.timescale.com

Technical documentation

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

www.monetdb.org/Documentation

docs.splunk.com/Documentation/Splunk

docs.timescale.com

Developer

Microsoft

MonetDB BV

Hughes Technologies

Splunk Inc.

Timescale

Initial release

1989

2004

1994

2003

2017

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

4.4, October 2021

2.15.0, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

free licenses can be provided

commercial

Limited free edition and free developer edition available

Open Source

Apache 2.0

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++

Server operating systems

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

Splunk Search Processing Language for search commands

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

HTTP REST

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Delphi
Java
Perl
PHP
Tcl

C#
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

yes, in SQL, C, R

yes

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

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 via remote tables

none

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

none

Multi-source replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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