DBMS > Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. Qdrant vs. RDFox

System Properties Comparison Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. Qdrant vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A high-performance vector database with neural network or semantic-based matching

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Vector DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	15.25
Rank	#38	Overall
	#23	Relational DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

aws.amazon.com/redshift

azure.microsoft.com/services/synapse-analytics

github.com/qdrant/qdrant
qdrant.tech

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/redshift

docs.microsoft.com/azure/synapse-analytics

qdrant.tech/documentation

docs.oxfordsemantic.tech

Developer

Amazon (based on PostgreSQL)

Microsoft

Qdrant

Oxford Semantic Technologies

Initial release

2012

2016

2021

2017

Current release

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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++

Rust

C++

Server operating systems

hosted

Docker
Linux
macOS
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

RDF schemas

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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.

Secondary indexes

restricted

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

RESTful HTTP API
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
PHP

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Collection-level replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

yes

Key-based authentication

Roles, resources, and access types

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