DBMS > Cassandra vs. Microsoft Azure SQL Database vs. Sphinx vs. SQream DB

System Properties Comparison Cassandra vs. Microsoft Azure SQL Database vs. Sphinx vs. SQream DB

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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

Open source search engine for searching in data from different sources, e.g. relational databases

a GPU-based, columnar RDBMS for big data analytics workloads

Primary database model

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	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Website

cassandra.apache.org

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

sphinxsearch.com

sqream.com

Technical documentation

cassandra.apache.org/doc/latest

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

sphinxsearch.com/docs

docs.sqream.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

Sphinx Technologies Inc.

SQream Technologies

Initial release

2008

2010

2001

2017

Current release

4.1.3, July 2023

V12

3.5.1, February 2023

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

GPL version 2, commercial licence available

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++

C++, CUDA, Haskell, Java, Scala

Server operating systems

BSD
Linux
OS X
Windows

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL 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

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

full-text index on all search fields

SQL

Support of SQL

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

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

Proprietary protocol

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

ADO.NET
JDBC
ODBC

Proprietary protocol

.Net
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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Transact SQL

user defined functions in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal and vertical partitioning

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

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

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users can be defined per object

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

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