DBMS > H2GIS vs. PlanetScale vs. RDF4J vs. Realm

System Properties Comparison H2GIS vs. PlanetScale vs. RDF4J vs. Realm

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Editorial information provided by DB-Engines

Name

Description

Spatial extension of H2

Scalable, distributed, serverless MySQL database platform built on top of Vitess

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Primary database model

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	0.00
Rank	#385	Overall
	#7	Spatial DBMS

Score	1.09
Rank	#178	Overall
	#82	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	7.18
Rank	#52	Overall
	#8	Document stores

Website

Technical documentation

www.h2gis.org/docs/home

planetscale.com/docs

rdf4j.org/documentation

realm.io/docs

Developer

CNRS

PlanetScale

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Realm, acquired by MongoDB in May 2019

Initial release

2013

2020

2004

2014

License

Commercial or Open Source

Open Source

LGPL 3.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

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

Java

Server operating systems

Docker
Linux
macOS

Linux
OS X
Unix
Windows

Android
Backend: server-less
iOS
Windows

Data scheme

yes

RDF Schemas

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

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
MySQL protocol
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Java
PHP
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

based on H2

yes

proprietary syntax

yes

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID at shard level

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

yes

based on H2

Users with fine-grained authorization concept

no user groups or roles

yes

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More resources

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