DBMS > Adabas vs. FatDB vs. Microsoft SQL Server vs. Riak KV vs. RisingWave

System Properties Comparison Adabas vs. FatDB vs. Microsoft SQL Server vs. Riak KV vs. RisingWave

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

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

used typically together with the Natural programming platform

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Microsofts flagship relational DBMS

Distributed, fault tolerant key-value store

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS

Key-value store

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

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	4.10
Rank	#82	Overall
	#9	Key-value stores

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

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

www.microsoft.com/en-us/sql-server

www.risingwave.com/database

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

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

docs.risingwave.com/docs/current/intro

Developer

Software AG

FatCloud

Microsoft

OpenSource, formerly Basho Technologies

RisingWave Labs

Initial release

1971

2012

1989

2009

2022

Current release

SQL Server 2022, November 2022

3.2.0, December 2022

1.2, September 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Apache version 2, commercial enterprise edition

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Erlang

Rust

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Windows

Linux
Windows

Linux
OS X

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Via inetgration in SQL Server

yes

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

JDBC
PostgreSQL wire protocol

Supported programming languages

Natural

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

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

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

in Natural

yes

via applications

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

UDFs in Python or Java

Triggers

yes

via applications

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

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor

yes, but depending on the SQL-Server Edition

selectable replication factor

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

Immediate 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

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)

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

yes, using Riak Security

Users and Roles

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