DBMS > Amazon Redshift vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. Qdrant

System Properties Comparison Amazon Redshift vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. Qdrant

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

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

Primary database model

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Vector DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

aws.amazon.com/redshift

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

nsdb.io

origodb.com

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.aws.amazon.com/redshift

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

nsdb.io/Architecture

origodb.com/docs

qdrant.tech/documentation

Developer

Amazon (based on PostgreSQL)

Microsoft

Robert Friberg et al

Qdrant

Initial release

2012

2010

2017

2009

under the name LiveDB

2021

Current release

V12

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

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, Scala

Rust

Server operating systems

hosted

Linux
macOS

Linux
Windows

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

Numbers, Strings, Geo, Boolean

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

can be achieved using .NET

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

All languages supporting JDBC/ODBC

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

Java
Scala

.Net

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

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

Source-replica replication

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

depending on model

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

Using Apache Lucene

yes

Write ahead log

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

Role based authorization

Key-based authentication

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