DBMS > eXtremeDB vs. GeoSpock vs. OpenQM vs. PostgreSQL vs. XTDB

System Properties Comparison eXtremeDB vs. GeoSpock vs. OpenQM vs. PostgreSQL vs. XTDB

Editorial information provided by DB-Engines

Name

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

Description

Natively in-memory DBMS with options for persistency, high-availability and clustering

Spatial and temporal data processing engine for extreme data scale

QpenQM is a high-performance, self-tuning, multi-value DBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Multivalue DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Secondary database models

Time Series DBMS

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.74
Rank	#223	Overall
	#103	Relational DBMS
	#18	Time Series DBMS

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.mcobject.com

geospock.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.postgresql.org

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

Technical documentation

www.mcobject.com/docs/extremedb.htm

www.postgresql.org/docs

www.xtdb.com/docs

Developer

McObject

GeoSpock

Rocket Software, originally Martin Phillips

PostgreSQL Global Development Group

www.postgresql.org/developer

Juxt Ltd.

Initial release

2001

1993

1989

1989: Postgres, 1996: PostgreSQL

2019

Current release

8.2, 2021

2.0, September 2019

3.4-12

16.3, May 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

Open Source

BSD

Open Source

MIT License

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.

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Implementation language

C and C++

Java, Javascript

Clojure

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

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

Data scheme

yes

with some exceptions

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.

support of XML interfaces available

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes

with the option: eXtremeSQL

ANSI SQL for query only (using Presto)

yes

standard with numerous extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

JDBC

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

HTTP REST
JDBC

Supported programming languages

.Net
C
C#
C++
Java
Lua
Python
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java

Server-side scripts

Stored procedures

yes

user defined functions

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

Triggers

yes

by defining events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning / sharding

Automatic sharding

yes

partitioning by range, list and (since PostgreSQL 11) by hash

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

Source-replica replication

other methods possible by using 3rd party extensions

yes, each node contains all data

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Access rights for users can be defined per table

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

eXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
» more

Competitive advantages

eXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
» more

Typical application scenarios

IoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more

Key customers

Schneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more

Market metrics

With hundreds of customers and over 30 million devices/applications using the product...
» more

Licensing and pricing models

For server use cases, there is a simple per-server license irrespective of the number...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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