DBMS > Altibase vs. Couchbase vs. Datomic vs. OrigoDB vs. RDF4J

System Properties Comparison Altibase vs. Couchbase vs. Datomic vs. OrigoDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Object oriented DBMS

RDF store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	18.46
Rank	#36	Overall
	#5	Document stores

Score	1.76
Rank	#145	Overall
	#66	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Website

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.couchbase.com

docs.datomic.com

origodb.com/docs

rdf4j.org/documentation

Developer

Altibase

Couchbase, Inc.

Cognitect

Robert Friberg et al

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

Initial release

1999

2011

2012

2009

under the name LiveDB

2004

Current release

v7.3, 2023, August 2023

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

1.0.6735, June 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

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

C++

C, C++, Go and Erlang

Java, Clojure

Java

Server operating systems

AIX
HP-UX
Linux

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

APIs and other access methods

JDBC
ODBC
Proprietary protocol

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

RESTful HTTP API

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C
C++
Java

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Clojure
Java

.Net

Java
PHP
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Transaction Functions

yes

Triggers

yes

via the TAP protocol

By using transaction functions

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic Sharding

none

But extensive use of caching in the application peers

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

ACID

Isolation support depends on the API used

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

Write ahead log

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

Ephemeral buckets

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Role based authorization

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