DBMS > Cassandra vs. Ingres vs. mSQL vs. Postgres-XL vs. SwayDB

System Properties Comparison Cassandra vs. Ingres vs. mSQL vs. Postgres-XL vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Well established RDBMS

mSQL (Mini SQL) is a simple and lightweight RDBMS

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Wide column store

Relational DBMS

Key-value store

Secondary database models

Vector DBMS

starting with release V5

Document store
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	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

cassandra.apache.org

www.actian.com/databases/ingres

hughestech.com.au/products/msql

www.postgres-xl.org

swaydb.simer.au

Technical documentation

cassandra.apache.org/doc/latest

docs.actian.com/ingres

www.postgres-xl.org/documentation

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Actian Corporation

Hughes Technologies

Simer Plaha

Initial release

2008

1974

originally developed at University Berkely in early 1970s

1994

2014

since 2012, originally named StormDB

2018

Current release

4.1.3, July 2023

11.2, May 2022

4.4, October 2021

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free licenses can be provided

Open Source

Mozilla public license

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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

Scala

Server operating systems

BSD
Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

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.

but tools for importing/exporting data from/to XML-files available

yes

XML type, but no XML query functionality

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

yes

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

distributed, parallel query execution

APIs and other access methods

Proprietary protocol

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Ingres Replicator

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

none

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

MVCC

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

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...
» 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

How Concide Built its Chat Platform with Enhanced Document Management for Legal Tech Professionals
23 May 2024

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

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.