DBMS > IBM Cloudant vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Netezza

System Properties Comparison IBM Cloudant vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

Database as a Service offering based on Apache CouchDB

Performant, highly scalable DBMS for AI and IoT applications

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store

Key-value store
Vector DBMS

Relational DBMS

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

Score	2.68
Rank	#106	Overall
	#20	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.ibm.com/products/cloudant

www.jaguardb.com

azure.microsoft.com/services/synapse-analytics

www.ibm.com/products/netezza

Technical documentation

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

docs.microsoft.com/azure/synapse-analytics

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Microsoft

IBM

Initial release

2010

2015

2016

2000

Current release

3.3 July 2023

License

Commercial or Open Source

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Erlang

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

Linux

hosted

Linux

included in appliance

Data scheme

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.

Secondary indexes

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

C#
Java
JavaScript
Objective-C
PHP
Ruby

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

C#
Java
PHP

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Transact SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

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.

User concepts

Access control

Access rights for users can be defined per database

rights management via user accounts

yes

Users with fine-grained authorization concept

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More resources

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