DBMS > 4D vs. Altibase vs. Drizzle vs. JanusGraph vs. Stardog

System Properties Comparison 4D vs. Altibase vs. Drizzle vs. JanusGraph vs. Stardog

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Application development environment with integrated database management system

An enterprise grade, high-performance RDBMS

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Graph DBMS

Graph DBMS
RDF store

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

developer.4d.com

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

docs.janusgraph.org

docs.stardog.com

Developer

4D, Inc

Altibase

Drizzle project, originally started by Brian Aker

Linux Foundation; originally developed as Titan by Aurelius

Stardog-Union

Initial release

1984

1999

2008

2017

2010

Current release

v20, April 2023

v7.3, 2023, August 2023

7.2.4, September 2012

0.6.3, February 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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

Server operating systems

OS X
Windows

AIX
HP-UX
Linux

FreeBSD
Linux
OS X

Linux
OS X
Unix
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

close to SQL 92

ANSI SQL-92

yes

with proprietary extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC
Proprietary protocol

JDBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

4D proprietary IDE
PHP

C
C++
Java

C
C++
Java
PHP

Clojure
Java
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

stored procedures and stored functions

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

hooks for callbacks inside the server can be used.

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Multi-source replication
Source-replica replication

yes

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

In-memory capabilities

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

yes

User concepts

Access control

Users and groups

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

User authentification and security via Rexster Graph Server

Access rights for users and roles

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