DBMS > Adabas vs. AnzoGraph DB vs. Axibase vs. Microsoft SQL Server vs. STSdb

System Properties Comparison Adabas vs. AnzoGraph DB vs. Axibase vs. Microsoft SQL Server vs. STSdb

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 graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Microsofts flagship relational DBMS

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

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	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

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

cambridgesemantics.com/anzograph

axibase.com/docs/atsd/finance

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

github.com/STSSoft/STSdb4

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

Developer

Software AG

Cambridge Semantics

Axibase Corporation

Microsoft

STS Soft SC

Initial release

1971

2018

2013

1989

2011

Current release

2.3, January 2021

15585

SQL Server 2022, November 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

free trial version available

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

restricted free version is available

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
Windows

Windows

Data scheme

yes

Schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

primitive types and user defined types (classes)

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

SPARQL and SPARQL* as primary query language. Cypher preview.

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

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

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

.NET Client API

Supported programming languages

Natural

C++
Java
Python

Go
Java
PHP
Python
R
Ruby

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

C#
Java

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates

yes

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

Automatic sharding

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 in MPP-Cluster

Source-replica replication

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

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)

Access rights for users and roles

fine grained access rights according to SQL-standard

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