DBMS > IBM Cloudant vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Riak TS

System Properties Comparison IBM Cloudant vs. JaguarDB vs. Microsoft Azure Synapse Analytics vs. Microsoft SQL Server vs. Riak TS

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

Microsofts flagship relational DBMS

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

Document store

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	2.85
Rank	#95	Overall
	#18	Document stores

Score	0.00
Rank	#385	Overall
	#61	Key-value stores
	#16	Vector DBMS

Score	18.98
Rank	#31	Overall
	#19	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Website

www.ibm.com/products/cloudant

www.jaguardb.com

azure.microsoft.com/services/synapse-analytics

www.microsoft.com/en-us/sql-server

Technical documentation

cloud.ibm.com/docs/Cloudant

www.jaguardb.com/support.html

docs.microsoft.com/azure/synapse-analytics

learn.microsoft.com/en-US/sql/sql-server

www.tiot.jp/riak-docs/riak/ts/latest

Developer

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

DataJaguar, Inc.

Microsoft

Open Source, formerly Basho Technologies

Initial release

2010

2015

2016

1989

2015

Current release

3.3 July 2023

SQL Server 2022, November 2022

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Erlang

C++

the server part. Clients available in other languages

C++

Erlang

Server operating systems

hosted

Linux

hosted

Linux
Windows

Linux
OS X

Data scheme

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.

yes

Secondary indexes

yes

restricted

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

yes, limited

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP API
Native Erlang Interface

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++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

yes

yes, but depending on the SQL-Server Edition

selectable replication factor

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

Eventual Consistency

Foreign keys

Referential integrity

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

yes

links between datasets can be stored

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.

yes

User concepts

Access control

Access rights for users can be defined per database

rights management via user accounts

yes

fine grained access rights according to SQL-standard

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