DBMS > Graph Engine vs. PostGIS vs. TempoIQ vs. Teradata vs. Ultipa

System Properties Comparison Graph Engine vs. PostGIS vs. TempoIQ vs. Teradata vs. Ultipa

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Spatial extension of PostgreSQL

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

A hybrid cloud data analytics software platform (Teradata Vantage)

High performance Graph DBMS supporting HTAP high availability cluster deployment

Primary database model

Graph DBMS
Key-value store

Secondary database models

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Score	0.19
Rank	#330	Overall
	#30	Graph DBMS

Website

www.graphengine.io

postgis.net

tempoiq.com (offline)

www.teradata.com

www.ultipa.com

Technical documentation

www.graphengine.io/docs/manual

postgis.net/documentation

docs.teradata.com

www.ultipa.com/document

Developer

Microsoft

TempoIQ

Teradata

Ultipa

Initial release

2010

2005

2012

1984

2019

Current release

3.4.2, February 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

MIT License

Open Source

GPL v2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

.NET and C

Server operating systems

.NET

hosted
Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API

HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

RESTful HTTP API

Supported programming languages

C#
C++
F#
Visual Basic

C#
Java
JavaScript

Node.js
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

C++
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

yes

based on PostgreSQL

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

Multi-source replication
Source-replica replication

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

based on PostgreSQL

simple authentication-based access control

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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2 April 2013, Paul Andlinger

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