DBMS > AllegroGraph vs. Altibase vs. Axibase vs. Couchbase vs. RDF4J

System Properties Comparison AllegroGraph vs. Altibase vs. Axibase vs. Couchbase vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

An enterprise grade, high-performance RDBMS

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

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	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

allegrograph.com

altibase.com

axibase.com/docs/atsd/finance

www.couchbase.com

rdf4j.org

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

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

docs.couchbase.com

rdf4j.org/documentation

Developer

Franz Inc.

Altibase

Axibase Corporation

Couchbase, Inc.

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

Initial release

2004

1999

2013

2011

2004

Current release

8.0, December 2023

v7.3, 2023, August 2023

15585

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

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open source edition discontinued with March 2023

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

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

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++

Java

C, C++, Go and Erlang

Java

Server operating systems

Linux
OS X
Windows

AIX
HP-UX
Linux

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

RDF schemas

yes

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

bulk load of XML files possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

ANSI SQL-92

SQL-like query language

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

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC
Proprietary protocol

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C
C++
Java

Go
Java
PHP
Python
R
Ruby

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

stored procedures and stored functions

yes

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

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Automatic Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Source-replica replication

Multi-source replication

including cross data center replication
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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Foreign keys

Referential integrity

yes

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

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

User concepts

Access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
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Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
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