DBMS > Adabas vs. Citus vs. Graph Engine vs. Microsoft Azure Cosmos DB vs. SWC-DB

System Properties Comparison Adabas vs. Citus vs. Graph Engine vs. Microsoft Azure Cosmos DB vs. SWC-DB

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 hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Globally distributed, horizontally scalable, multi-model database service

A high performance, scalable Wide Column DBMS

Primary database model

Multivalue DBMS

Relational DBMS

Graph DBMS
Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Document store

Spatial DBMS

Time Series DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

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

www.citusdata.com

www.graphengine.io

azure.microsoft.com/services/cosmos-db

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.citusdata.com

www.graphengine.io/docs/manual

learn.microsoft.com/azure/cosmos-db

Developer

Software AG

Microsoft

Alex Kashirin

Initial release

1971

2010

2014

2020

Current release

8.1, December 2018

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

MIT License

commercial

Open Source

GPL V3

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

.NET and C

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

.NET

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Proprietary protocol
Thrift

Supported programming languages

Natural

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
C++
F#
Visual Basic

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C++

Server-side scripts

Stored procedures

in Natural

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Source-replica replication

other methods possible by using 3rd party extensions

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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)

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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