DBMS > Datomic vs. gStore vs. InterSystems Caché vs. RocksDB

System Properties Comparison Datomic vs. gStore vs. InterSystems Caché vs. RocksDB

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

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.

A multi-model DBMS and application server

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Graph DBMS
RDF store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Document store

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	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.datomic.com

en.gstore.cn

www.intersystems.com/products/cache

rocksdb.org

Technical documentation

docs.datomic.com

en.gstore.cn/#/enDocs

docs.intersystems.com

github.com/facebook/rocksdb/wiki

Developer

Cognitect

InterSystems

Facebook, Inc.

Initial release

2012

2016

1997

2013

Current release

1.0.6735, June 2023

1.2, November 2023

2018.1.4, May 2020

8.11.4, April 2024

License

Commercial or Open Source

commercial

limited edition free

Open Source

BSD

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java, Clojure

C++

Server operating systems

All OS with a Java VM

Linux

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free and OWL/RDFS-schema support

depending on used data model

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

HTTP API
SPARQL 1.1

.NET Client API
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Clojure
Java

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

C#
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

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

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Source-replica replication

yes

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

yes

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

User concepts

Access control

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

Access rights for users, groups and roles

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