DBMS > Adabas vs. Cubrid vs. Hypertable vs. JaguarDB vs. Microsoft SQL Server

System Properties Comparison Adabas vs. Cubrid vs. Hypertable vs. JaguarDB vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

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

used typically together with the Natural programming platform

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

An open source BigTable implementation based on distributed file systems such as Hadoop

Performant, highly scalable DBMS for AI and IoT applications

Microsofts flagship relational DBMS

Primary database model

Multivalue DBMS

Relational DBMS

Wide column store

Key-value store
Vector DBMS

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	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

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

cubrid.com (korean)
cubrid.org (english)

www.jaguardb.com

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

Technical documentation

cubrid.org/manuals

www.jaguardb.com/support.html

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

Developer

Software AG

CUBRID Corporation, CUBRID Foundation

Hypertable Inc.

DataJaguar, Inc.

Microsoft

Initial release

1971

2008

2009

2015

1989

Current release

11.0, January 2021

0.9.8.11, March 2016

3.3 July 2023

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

Open Source

GPL V3.0

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++, Java

C++

the server part. Clients available in other languages

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
Windows

Linux
OS X
Windows

an inofficial Windows port is available

Linux

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

Secondary indexes

yes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

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
ODBC
OLE DB

C++ API
Thrift

JDBC
ODBC

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

Supported programming languages

Natural

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

C++
Java
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

in Natural

Java Stored Procedures

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

none

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

selectable replication factor on file system level

Multi-source replication

yes, but depending on the SQL-Server Edition

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

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

rights management via user accounts

fine grained access rights according to SQL-standard

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