DBMS > Adabas vs. Apache IoTDB vs. Microsoft SQL Server vs. NuoDB vs. Stardog

System Properties Comparison Adabas vs. Apache IoTDB vs. Microsoft SQL Server vs. NuoDB vs. Stardog

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

Microsofts flagship relational DBMS

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

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	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.94
Rank	#197	Overall
	#92	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

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

iotdb.apache.org

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

www.3ds.com/nuodb-distributed-sql-database

www.stardog.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

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

doc.nuodb.com

docs.stardog.com

Developer

Software AG

Apache Software Foundation

Microsoft

Dassault Systèmes

originally NuoDB, Inc.

Stardog-Union

Initial release

1971

2018

1989

2013

2010

Current release

1.1.0, April 2023

SQL Server 2022, November 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

commercial

limited edition free

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

All OS with a Java VM (>= 1.8)

Linux
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL-like query language

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

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
Native API

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

ADO.NET
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Natural

C
C#
C++
Go
Java
Python
Scala

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

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

in Natural

yes

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

Java, SQL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

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

data is dynamically stored/cached on the nodes where it is read/written

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes, but depending on the SQL-Server Edition

yes

Managed transparently by NuoDB

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

tunable commit protocol

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

yes

User concepts

Access control

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

yes

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

Access rights for users and roles

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