DBMS > atoti vs. Microsoft SQL Server vs. OpenMLDB vs. RDF4J

System Properties Comparison atoti vs. Microsoft SQL Server vs. OpenMLDB vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

Microsofts flagship relational DBMS

An open-source machine learning database that provides a feature platform for training and inference

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

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS

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

Score	0.45
Rank	#253	Overall
	#13	Object oriented DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

atoti.io

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

openmldb.ai

rdf4j.org

Technical documentation

docs.atoti.io

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

openmldb.ai/docs/zh/main

rdf4j.org/documentation

Developer

ActiveViam

Microsoft

4 Paradigm Inc.

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

Initial release

1989

2020

2004

Current release

SQL Server 2022, November 2022

2024-2 February 2024

License

Commercial or Open Source

commercial

free versions available

commercial

restricted free version is available

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

C++, Java, Scala

Java

Server operating systems

Linux
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

Fixed schema

yes

RDF Schemas

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

Multidimensional Expressions (MDX)

yes

APIs and other access methods

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

JDBC
SQLAlchemy

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

C++
Go
Java
Python
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

Python

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

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

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Source-replica replication

none

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, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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