DBMS > Microsoft SQL Server vs. mSQL vs. SiteWhere vs. Splice Machine vs. XTDB

System Properties Comparison Microsoft SQL Server vs. mSQL vs. SiteWhere vs. Splice Machine vs. XTDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

M2M integration platform for persisting/querying time series data

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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Trend Chart

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

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

hughestech.com.au/products/msql

github.com/sitewhere/sitewhere

splicemachine.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

sitewhere1.sitewhere.io/index.html

splicemachine.com/how-it-works

www.xtdb.com/docs

Developer

Microsoft

Hughes Technologies

SiteWhere

Splice Machine

Juxt Ltd.

Initial release

1989

1994

2010

2014

2019

Current release

SQL Server 2022, November 2022

4.4, October 2021

3.1, March 2021

1.19, September 2021

License

Commercial or Open Source

commercial

restricted free version is available

commercial

free licenses can be provided

Open Source

Common Public Attribution License Version 1.0

Open Source

AGPL 3.0, commercial license available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

Clojure

Server operating systems

Linux
Windows

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

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

predefined scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

A subset of ANSI SQL is implemented

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

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

JDBC
ODBC

HTTP REST

JDBC
Native Spark Datasource
ODBC

HTTP REST
JDBC

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

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

Clojure
Java

Server-side scripts

Stored procedures

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

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

Sharding

based on HBase

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

none

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

yes, each node contains all data

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

none

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Users with fine-grained authorization concept

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

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