DBMS > GigaSpaces vs. IBM Cloudant vs. Microsoft Azure Synapse Analytics

System Properties Comparison GigaSpaces vs. IBM Cloudant vs. Microsoft Azure Synapse Analytics

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Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Database as a Service offering based on Apache CouchDB

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Document store

Relational DBMS

Secondary database models

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Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Website

www.gigaspaces.com

www.ibm.com/products/cloudant

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.gigaspaces.com/latest/landing.html

cloud.ibm.com/docs/Cloudant

docs.microsoft.com/azure/synapse-analytics

Developer

Gigaspaces Technologies

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Microsoft

Initial release

2000

2010

2016

Current release

15.5, September 2020

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

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

Java, C++, .Net

Erlang

C++

Server operating systems

Linux
macOS
Solaris
Windows

hosted

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

yes

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C++
Java
Python
Scala

C#
Java
JavaScript
Objective-C
PHP
Ruby

C#
Java
PHP

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

Transact SQL

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

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

Role-based access control

Access rights for users can be defined per database

yes

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