DBMS > Drizzle vs. IBM Cloudant vs. SiteWhere vs. Teradata

System Properties Comparison Drizzle vs. IBM Cloudant vs. SiteWhere vs. Teradata

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Database as a Service offering based on Apache CouchDB

M2M integration platform for persisting/querying time series data

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

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	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

www.ibm.com/products/cloudant

github.com/sitewhere/sitewhere

www.teradata.com

Technical documentation

cloud.ibm.com/docs/Cloudant

sitewhere1.sitewhere.io/index.html

docs.teradata.com

Developer

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

SiteWhere

Teradata

Initial release

2008

2010

1984

Current release

7.2.4, September 2012

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

GNU GPL

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

C++

Erlang

Java

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
OS X
Windows

hosted
Linux

Data scheme

yes

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

with proprietary extensions

yes

SQL 2016 + extensions

APIs and other access methods

JDBC

RESTful HTTP/JSON API

HTTP REST

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

Supported programming languages

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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

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