DBMS > Altibase vs. AnzoGraph DB vs. Firebase Realtime Database vs. IBM Db2 vs. MySQL

System Properties Comparison Altibase vs. AnzoGraph DB vs. Firebase Realtime Database vs. IBM Db2 vs. MySQL

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Common in IBM host environments, 2 different versions for host and Windows/Linux

Widely used open source RDBMS

Primary database model

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS

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

Score	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	127.49
Rank	#8	Overall
	#5	Relational DBMS

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Website

altibase.com

cambridgesemantics.com/anzograph

firebase.google.com/products/realtime-database

www.ibm.com/products/db2

www.mysql.com

Technical documentation

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

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

firebase.google.com/docs/database

www.ibm.com/docs/en/db2

dev.mysql.com/doc

Developer

Altibase

Cambridge Semantics

Google

acquired by Google 2014

IBM

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

1999

2018

2012

1983

host version

1995

Current release

v7.3, 2023, August 2023

2.3, January 2021

12.1, October 2016

8.3.0, January 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free trial version available

commercial

free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

C and C++

Server operating systems

AIX
HP-UX
Linux

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

ANSI SQL-92

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
C++
Java

C++
Java
Python

Java
JavaScript
Objective-C

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions and aggregates

limited functionality with using 'rules'

yes

proprietary syntax

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding

only with Windows/Unix/Linux Version

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication in MPP-Cluster

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

not needed in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

fine grained access rights according to SQL-standard

Access rights for users and roles

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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