DBMS > Fauna vs. SiteWhere vs. Teradata

System Properties Comparison Fauna vs. SiteWhere vs. Teradata

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

M2M integration platform for persisting/querying time series data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	0.06
Rank	#367	Overall
	#36	Time Series DBMS

Score	47.84
Rank	#21	Overall
	#15	Relational DBMS

Website

fauna.com

github.com/sitewhere/sitewhere

www.teradata.com

Technical documentation

docs.fauna.com

sitewhere1.sitewhere.io/index.html

docs.teradata.com

Developer

Fauna, Inc.

SiteWhere

Teradata

Initial release

2014

2010

1984

Current release

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

commercial

Open Source

Common Public Attribution License Version 1.0

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.

Implementation language

Scala

Java

Server operating systems

hosted

Linux
OS X
Windows

hosted
Linux

Data scheme

schema-free

predefined scheme

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

yes

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

SQL

Support of SQL

yes

SQL 2016 + extensions

APIs and other access methods

RESTful HTTP API

HTTP REST

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

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

Server-side scripts

Stored procedures

user defined functions

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

based on HBase

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Teradata is the most popular data warehouse DBMS
2 April 2013, Paul Andlinger

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Recent citations in the news

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