DBMS > PostGIS vs. Quasardb vs. TimescaleDB vs. Trafodion

System Properties Comparison PostGIS vs. Quasardb vs. TimescaleDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Spatial extension of PostgreSQL

Distributed, high-performance timeseries database

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Spatial DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

postgis.net/documentation

doc.quasar.ai/master

docs.timescale.com

trafodion.apache.org/documentation.html

Developer

quasardb

Timescale

Apache Software Foundation, originally developed by HP

Initial release

2005

2009

2017

2014

Current release

3.4.2, February 2024

3.14.1, January 2024

2.13.0, November 2023

2.3.0, February 2019

License

Commercial or Open Source

Open Source

GPL v2.0

commercial

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

Open Source

Apache 2.0

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++

C++, Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

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

full PostgreSQL SQL syntax

yes

APIs and other access methods

HTTP API

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

ADO.NET
JDBC
ODBC

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

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

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

based on PostgreSQL

Sharding

consistent hashing

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

Source-replica replication with selectable replication factor

Source-replica replication with hot standby and reads on replicas

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via user defined functions and HBase

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

User concepts

Access control

yes

based on PostgreSQL

Cryptographically strong user authentication and audit trail

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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