DBMS > Adabas vs. GigaSpaces vs. Kinetica vs. SAP SQL Anywhere vs. SQLite

System Properties Comparison Adabas vs. GigaSpaces vs. Kinetica vs. SAP SQL Anywhere vs. SQLite

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

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

Fully vectorized database across both GPUs and CPUs

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Widely used embeddable, in-process RDBMS

Primary database model

Multivalue DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Spatial DBMS
Time Series DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	4.57
Rank	#78	Overall
	#43	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.gigaspaces.com

www.kinetica.com

www.sap.com/products/technology-platform/sql-anywhere.html

www.sqlite.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

docs.kinetica.com

help.sap.com/docs/SAP_SQL_Anywhere

www.sqlite.org/docs.html

Developer

Software AG

Gigaspaces Technologies

Kinetica

SAP

formerly Sybase

Dwayne Richard Hipp

Initial release

1971

2000

2012

1992

2000

Current release

15.5, September 2020

7.1, August 2021

17, July 2015

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

Public Domain

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.

Implementation language

Java, C++, .Net

C, C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
macOS
Solaris
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

server-less

Data scheme

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-99 for query and DML statements

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API

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

with add-on software Adabas SOA Gateway

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

JDBC
ODBC
RESTful HTTP API

ADO.NET
HTTP API
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Natural

.Net
C++
Java
Python
Scala

C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

in Natural

yes

user defined functions

yes, in C/C++, Java, .Net or Perl

Triggers

yes, event driven architecture

yes

triggers when inserted values for one or more columns fall within a specified range

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Source-replica replication

Database mirroring

none

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 or Eventual Consistency depending on configuration

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

via file-system locks

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

GPU vRAM or System RAM

yes

User concepts

Access control

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

Role-based access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

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