DBMS > Adabas vs. Bangdb vs. Firebird vs. GridGain vs. JaguarDB

System Properties Comparison Adabas vs. Bangdb vs. Firebird vs. GridGain vs. JaguarDB

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Converged and high performance database for device data, events, time series, document and graph

Firebird is an open source RDBMS forked from Borland's InterBase

GridGain is an in-memory computing platform, built on Apache Ignite

Performant, highly scalable DBMS for AI and IoT applications

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store
Vector DBMS

Secondary database models

Spatial DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	20.50
Rank	#30	Overall
	#18	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

Technical documentation

docs.bangdb.com

www.firebirdsql.org/en/reference-manuals

www.gridgain.com/docs/index.html

www.jaguardb.com/support.html

Developer

Software AG

Sachin Sinha, BangDB

Firebird Foundation

GridGain Systems, Inc.

DataJaguar, Inc.

Initial release

1971

2012

2000

As fork of Borland's InterBase

2007

2015

Current release

BangDB 2.0, October 2021

5.0.0, January 2024

GridGain 8.5.1

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

BSD 3

Open Source

Initial Developer's Public License

commercial

Open Source

GPL V3.0

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 and C++

Java, C++, .Net

C++

the server part. Clients available in other languages

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL like support with command line tool

yes

ANSI-99 for query and DML statements, subset of DDL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

Proprietary protocol
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC

Supported programming languages

Natural

C
C#
C++
Java
Python

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

in Natural

PSQL

yes (compute grid and cache interceptors can be used instead)

Triggers

yes, Notifications (with Streaming only)

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor, Knob for CAP (enterprise version only)

Source-replica replication

yes (replicated cache)

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

yes (enterprise version only)

Users with fine-grained authorization concept

Security Hooks for custom implementations

rights management via user accounts

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