DBMS > Adabas vs. Cassandra vs. Stardog vs. TigerGraph

System Properties Comparison Adabas vs. Cassandra vs. Stardog vs. TigerGraph

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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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

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

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

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

cassandra.apache.org

www.stardog.com

www.tigergraph.com

Technical documentation

cassandra.apache.org/doc/latest

docs.stardog.com

docs.tigergraph.com

Developer

Software AG

Apache Software Foundation

Apache top level project, originally developped by Facebook

Stardog-Union

Initial release

1971

2008

2010

2017

Current release

4.1.3, July 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

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

commercial

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

BSD
Linux
OS X
Windows

Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like SELECT, DML and DDL statements (CQL)

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

SQL-like query language (GSQL)

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

CQL (Cassandra Query Language, an SQL-like language)
Thrift

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Natural

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

no "single point of failure"

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

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

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

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 can be defined per object

Access rights for users and roles

Role-based access control

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Cassandra is used by 40% of the Fortune 100.
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Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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