DBMS > H2GIS vs. OushuDB vs. Speedb

System Properties Comparison H2GIS vs. OushuDB vs. Speedb

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

An embeddable, high performance key-value store optimized for write-intensive workloads, which can be used as a drop-in replacement for RocksDB

Primary database model

Spatial DBMS

Relational DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.00
Rank	#389	Overall
	#7	Spatial DBMS

Score	0.07
Rank	#351	Overall
	#152	Relational DBMS

Score	0.16
Rank	#326	Overall
	#47	Key-value stores

Website

www.h2gis.org

www.oushu.com/product/oushuDB

www.speedb.io

Technical documentation

www.h2gis.org/docs/home

www.oushu.com/documentation

Developer

CNRS

Oushu

Speedb

Initial release

2013

2020

Current release

4.0.1, August 2020

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Apache Version 2.0; commercial license available

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

C++

Server operating systems

Linux

Linux
Windows

Data scheme

yes

schema-free

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

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC

Supported programming languages

Java

C
C++

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

yes

based on H2

Kerberos, SSL and role based access

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