DBMS > Adabas vs. AnzoGraph DB vs. Google Cloud Bigtable vs. SQLite

System Properties Comparison Adabas vs. AnzoGraph DB vs. Google Cloud Bigtable vs. SQLite

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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

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Widely used embeddable, in-process RDBMS

Primary database model

Multivalue DBMS

Graph DBMS
RDF store

Key-value store
Wide column store

Relational DBMS

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

Score	2.64
Rank	#104	Overall
	#1	Multivalue DBMS

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

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

cambridgesemantics.com/anzograph

cloud.google.com/bigtable

www.sqlite.org

Technical documentation

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

cloud.google.com/bigtable/docs

www.sqlite.org/docs.html

Developer

Software AG

Cambridge Semantics

Google

Dwayne Richard Hipp

Initial release

1971

2018

2015

2000

Current release

2.3, January 2021

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

server-less

Data scheme

yes

Schema-free and OWL/RDFS-schema support

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

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

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Natural

C++
Java
Python

C#
C++
Go
Java
JavaScript (Node.js)
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Automatic sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication in MPP-Cluster

Internal replication in Colossus, and regional replication between two clusters in different zones

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

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

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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