DBMS > Citus vs. GeoSpock vs. Microsoft SQL Server vs. Tibero vs. TimescaleDB

System Properties Comparison Citus vs. GeoSpock vs. Microsoft SQL Server vs. Tibero vs. TimescaleDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Spatial and temporal data processing engine for extreme data scale

Microsofts flagship relational DBMS

A secure RDBMS, designed for easy portability from Oracle

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

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1.78
Rank	#140	Overall
	#64	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.citusdata.com

geospock.com

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

us.tmaxsoft.com/products/tibero

www.timescale.com

Technical documentation

docs.citusdata.com

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

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

docs.timescale.com

Developer

GeoSpock

Microsoft

TmaxSoft

Timescale

Initial release

2010

1989

2003

2017

Current release

8.1, December 2018

2.0, September 2019

SQL Server 2022, November 2022

6, April 2015

2.15.0, May 2024

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

restricted free version is available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Javascript

C++

C and Assembler

Server operating systems

Linux

hosted

Linux
Windows

AIX
HP-UX
Linux
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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

standard, with numerous extensions

ANSI SQL for query only (using Presto)

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

JDBC

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

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

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

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

Persistent Stored Procedure (PSM)

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

Sharding

Automatic sharding

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

horizontal partitioning

by range, hash, list or composite

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

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

In-memory capabilities

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

yes

planned for next version

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

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

fine grained access rights according to SQL-standard

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