DBMS > Adabas vs. EsgynDB vs. Ingres vs. Microsoft Azure Cosmos DB vs. Riak KV

System Properties Comparison Adabas vs. EsgynDB vs. Ingres vs. Microsoft Azure Cosmos DB vs. Riak KV

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Well established RDBMS

Globally distributed, horizontally scalable, multi-model database service

Distributed, fault tolerant key-value store

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

with links between data sets and object tags for the creation of secondary indexes

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	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

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

www.esgyn.cn

www.actian.com/databases/ingres

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.actian.com/ingres

learn.microsoft.com/azure/cosmos-db

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Software AG

Esgyn

Actian Corporation

Microsoft

OpenSource, formerly Basho Technologies

Initial release

1971

2015

1974

originally developed at University Berkely in early 1970s

2014

2009

Current release

11.2, May 2022

3.2.0, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Erlang

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Linux
OS X

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All properties auto-indexed by default

restricted

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

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
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

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

HTTP API
Native Erlang Interface

Supported programming languages

Natural

All languages supporting JDBC/ODBC/ADO.Net

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

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

yes

JavaScript

Erlang

Triggers

yes

JavaScript

yes

pre-commit hooks and post-commit hooks

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

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication between multi datacenters

Ingres Replicator

yes

Implicit feature of the cloud service

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

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

Eventual Consistency

Foreign keys

Referential integrity

yes

links between data sets can be stored

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

MVCC

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.

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

yes, using Riak Security

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