DBMS > Dgraph vs. Microsoft Azure SQL Database vs. RDF4J vs. ReductStore

System Properties Comparison Dgraph vs. Microsoft Azure SQL Database vs. RDF4J vs. ReductStore

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Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

Database as a Service offering with high compatibility to Microsoft SQL Server

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

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.

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	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

dgraph.io

azure.microsoft.com/en-us/products/azure-sql/database

rdf4j.org

github.com/reductstore
www.reduct.store

Technical documentation

dgraph.io/docs

docs.microsoft.com/en-us/azure/azure-sql

rdf4j.org/documentation

www.reduct.store/docs

Developer

Dgraph Labs, Inc.

Microsoft

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

ReductStore LLC

Initial release

2016

2010

2004

2023

Current release

V12

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Business Source License 1.1

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++, Rust

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

schema-free

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

yes

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

ADO.NET
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API

Supported programming languages

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

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

Java
PHP
Python

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

yes, with always 3 replicas available

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

Durability

Support for making data persistent

yes

in-memory storage is supported as well

User concepts

Access control

Planned for future releases

fine grained access rights according to SQL-standard

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