DBMS > Microsoft SQL Server vs. ReductStore vs. Stardog vs. TimescaleDB

System Properties Comparison Microsoft SQL Server vs. ReductStore vs. Stardog vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

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

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

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

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

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

github.com/reductstore
www.reduct.store

www.stardog.com

www.timescale.com

Technical documentation

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

www.reduct.store/docs

docs.stardog.com

docs.timescale.com

Developer

Microsoft

ReductStore LLC

Stardog-Union

Timescale

Initial release

1989

2023

2010

2017

Current release

SQL Server 2022, November 2022

1.9, March 2024

7.3.0, May 2020

2.15.0, May 2024

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Business Source License 1.1

commercial

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

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C++, Rust

Java

Server operating systems

Linux
Windows

Docker
Linux
macOS
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

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

yes

full PostgreSQL SQL syntax

APIs and other access methods

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

HTTP API

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

C++
JavaScript (Node.js)
Python
Rust

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

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

user defined functions and aggregates, HTTP Server extensions in Java

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

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

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

Multi-source replication in HA-Cluster

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships 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

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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