DBMS > Amazon Redshift vs. Drizzle vs. IBM Cloudant vs. JaguarDB vs. Microsoft Azure Table Storage

System Properties Comparison Amazon Redshift vs. Drizzle vs. IBM Cloudant vs. JaguarDB vs. Microsoft Azure Table Storage

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

Large scale data warehouse service for use with business intelligence tools

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

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Wide column store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

aws.amazon.com/redshift

www.ibm.com/products/cloudant

www.jaguardb.com

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

docs.aws.amazon.com/redshift

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

Developer

Amazon (based on PostgreSQL)

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Microsoft

Initial release

2012

2008

2010

2015

2012

Current release

7.2.4, September 2012

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

Open Source

GPL V3.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Erlang

C++

the server part. Clients available in other languages

Server operating systems

hosted

FreeBSD
Linux
OS X

hosted

Linux

hosted

Data scheme

yes

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

with proprietary extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

JDBC

RESTful HTTP/JSON API

JDBC
ODBC

RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

View functions (Map-Reduce) in JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

atomic operations within a document possible

optimistic locking

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

fine grained access rights according to SQL-standard

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

rights management via user accounts

Access rights based on private key authentication or shared access signatures

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