DBMS > Adabas vs. Apache Drill vs. Datomic vs. Microsoft SQL Server vs. MySQL

System Properties Comparison Adabas vs. Apache Drill vs. Datomic vs. Microsoft SQL Server vs. MySQL

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

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Microsofts flagship relational DBMS

Widely used open source RDBMS

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

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

drill.apache.org

www.datomic.com

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

www.mysql.com

Technical documentation

drill.apache.org/docs

docs.datomic.com

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

dev.mysql.com/doc

Developer

Software AG

Apache Software Foundation

Cognitect

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

1971

2012

1989

1995

Current release

1.20.3, January 2023

1.0.6735, June 2023

SQL Server 2022, November 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

limited edition free

commercial

restricted free version is available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

C++

C and C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

FreeBSD
Linux
OS X
Solaris
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

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL SELECT statement is SQL:2003 compliant

yes

with proprietary extensions

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
ODBC
RESTful HTTP API

RESTful HTTP API

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

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Natural

C++

Clojure
Java

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

in Natural

user defined functions

yes

Transaction Functions

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

yes

proprietary syntax

Triggers

By using transaction functions

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

But extensive use of caching in the application peers

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

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

But extensive use of caching in the application peers

yes, but depending on the SQL-Server Edition

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

recommended only for testing and development

yes

User concepts

Access control

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

Depending on the underlying data source

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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