DBMS > Adabas vs. Drizzle vs. Microsoft SQL Server vs. RDF4J vs. Typesense

System Properties Comparison Adabas vs. Drizzle vs. Microsoft SQL Server vs. RDF4J vs. Typesense

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

used typically together with the Natural programming platform

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Microsofts flagship relational DBMS

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.91
Rank	#203	Overall
	#14	Search engines

Website

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

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

rdf4j.org

typesense.org

Technical documentation

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

rdf4j.org/documentation

typesense.org/docs

Developer

Software AG

Drizzle project, originally started by Brian Aker

Microsoft

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

1971

2008

1989

2004

2015

Current release

7.2.4, September 2012

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

FreeBSD
Linux
OS X

Linux
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

yes

RDF Schemas

schema-free

pre-defined schema optional

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

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

with proprietary extensions

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

JDBC

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

Natural

C
C++
Java
PHP

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

Java
PHP
Python

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

in Natural

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

yes

Triggers

hooks for callbacks inside the server can be used.

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

yes, but depending on the SQL-Server Edition

none

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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