DBMS > Cassandra vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. OushuDB

System Properties Comparison Cassandra vs. Microsoft Azure SQL Database vs. NSDb vs. OrigoDB vs. OushuDB

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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 data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Wide column store

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

Document store
Graph DBMS
Spatial DBMS

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

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	0.04
Rank	#363	Overall
	#154	Relational DBMS

Website

cassandra.apache.org

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

nsdb.io

origodb.com

www.oushu.com/product/oushuDB

Technical documentation

cassandra.apache.org/doc/latest

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

nsdb.io/Architecture

origodb.com/docs

www.oushu.com/documentation

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

Robert Friberg et al

Oushu

Initial release

2008

2010

2017

2009

under the name LiveDB

Current release

4.1.3, July 2023

V12

4.0.1, August 2020

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0

Open Source

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++

Java, Scala

Server operating systems

BSD
Linux
OS X
Windows

hosted

Linux
macOS

Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

yes

SQL-like query language

Full-featured ANSI SQL support

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

Java
Scala

.Net

C
C++

Server-side scripts

Stored procedures

Transact SQL

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes, with always 3 replicas available

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

Role based authorization

Kerberos, SSL and role based access

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

News

Astra Vectorize: Generate Vector Embeddings with 1 Line of Code
22 May 2024

GitHub Copilot + DataStax Astra DB: Build GenAI Apps 100x Faster
21 May 2024

Empowering On-Premises Deployments with Generative AI: Introducing Vector Search for a Self-Managed Modern Architecture
15 May 2024

Tips and Tricks for the DataStax Astra CLI
7 May 2024

How to Build a Crystal Image Search App with Vector Search
25 April 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.