DBMS > Datomic vs. gStore vs. HyperSQL vs. Realm

System Properties Comparison Datomic vs. gStore vs. HyperSQL vs. Realm

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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

A native Graph DBMS to store and maintain very large RDF datasets.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

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

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Website

Technical documentation

docs.datomic.com

en.gstore.cn/#/enDocs

hsqldb.org/web/hsqlDocsFrame.html

realm.io/docs

Developer

Cognitect

Realm, acquired by MongoDB in May 2019

Initial release

2012

2016

2001

2014

Current release

1.0.6735, June 2023

1.2, November 2023

2.7.2, June 2023

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

Open Source

based on BSD license

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

C++

Java

Server operating systems

All OS with a Java VM

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Android
Backend: server-less
iOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

APIs and other access methods

RESTful HTTP API

HTTP API
SPARQL 1.1

HTTP API

JDBC via HTTP
JDBC
ODBC

Supported programming languages

Clojure
Java

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

All languages supporting JDBC/ODBC
Java

.Net
Java

with Android only
Objective-C
React Native
Swift

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Java, SQL

runs within the applications so server-side scripts are unnecessary

Triggers

By using transaction functions

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

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

In-Memory realm

User concepts

Access control

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

yes

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