DBMS > Adabas vs. Citus vs. GigaSpaces vs. Machbase Neo vs. Microsoft SQL Server

System Properties Comparison Adabas vs. Citus vs. GigaSpaces vs. Machbase Neo vs. Microsoft SQL Server

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

TimeSeries DBMS for AIoT and BigData

Microsofts flagship relational DBMS

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Relational DBMS

Secondary database models

Document store

Graph DBMS
Search engine

Document store
Graph DBMS
Spatial DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

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

www.citusdata.com

www.gigaspaces.com

machbase.com

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

Technical documentation

docs.citusdata.com

docs.gigaspaces.com/latest/landing.html

machbase.com/dbms

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

Developer

Software AG

Gigaspaces Technologies

Machbase

Microsoft

Initial release

1971

2010

2000

2013

1989

Current release

8.1, December 2018

15.5, September 2020

V8.0, August 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

Apache Version 2; Commercial licenses available

commercial

free test version available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java, C++, .Net

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Linux
Windows

Data scheme

yes

schema-free

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.

yes

specific XML type available, but no XML query functionality

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

standard, with numerous extensions

SQL-99 for query and DML statements

SQL-like query language

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

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

Supported programming languages

Natural

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

.Net
C++
Java
Python
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

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

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

Triggers

yes

yes, event driven architecture

yes

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

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

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

volatile and lookup table

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

Role-based access control

simple password-based access control

fine grained access rights according to SQL-standard

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