DBMS > Datomic vs. H2GIS vs. openGauss

System Properties Comparison Datomic vs. H2GIS vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Spatial extension of H2

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	1.11
Rank	#175	Overall
	#79	Relational DBMS

Website

www.datomic.com

www.h2gis.org

gitee.com/opengauss
opengauss.org

Technical documentation

docs.datomic.com

www.h2gis.org/docs/home

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

Cognitect

CNRS

Huawei and openGauss community

Initial release

2012

2013

2019

Current release

1.0.7180, July 2024

3.0, March 2022

License

Commercial or Open Source

commercial

limited edition free

Open Source

LGPL 3.0

Open Source

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

Java, Clojure

Java

C, C++, Java

Server operating systems

All OS with a Java VM

Linux

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL 2011

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

Supported programming languages

Clojure
Java

Java

C
C++
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

based on H2

yes

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

based on H2

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

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

yes

based on H2

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

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