DBMS > Apache Cassandra vs. EXASOL vs. Firebase Realtime Database vs. Teradata

System Properties Comparison Apache Cassandra vs. EXASOL vs. Firebase Realtime Database vs. Teradata

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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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Secondary database models

Vector DBMS

starting with release V5

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	41.47
Rank	#22	Overall
	#15	Relational DBMS

Website

cassandra.apache.org

www.exasol.com

firebase.google.com/products/realtime-database

www.teradata.com

Technical documentation

cassandra.apache.org/doc/latest

www.exasol.com/resources

firebase.google.com/docs/database

docs.teradata.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Exasol

Google

acquired by Google 2014

Teradata

Initial release

2008

2000

2012

1984

Current release

5.0-rc1, July 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache version 2

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

Server operating systems

BSD
Linux
OS X
Windows

hosted

hosted
Linux

Data scheme

schema-free

yes

schema-free

yes

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.

yes

Secondary indexes

restricted

only equality queries, not always the best performing solution

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

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

yes

SQL 2016 + extensions

APIs and other access methods

Proprietary protocol

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

.Net
JDBC
ODBC
WebSocket

Android
iOS
JavaScript API
RESTful HTTP API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java
Lua
Python
R

Java
JavaScript
Objective-C

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

user defined functions

limited functionality with using 'rules'

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication
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

if the client is offline
Immediate Consistency

if the client is online

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

yes

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

Access rights for users can be defined per object

Access rights for users, groups and roles according to SQL-standard

yes, based on authentication and database rules

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

Apache 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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