DBMS > GridGain vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. SwayDB

System Properties Comparison GridGain vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Database as a Service offering with high compatibility to Microsoft SQL Server

Microsofts flagship relational DBMS

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.00
Rank	#384	Overall
	#60	Key-value stores

Website

www.gridgain.com

azure.microsoft.com/en-us/products/azure-sql/database

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

swaydb.simer.au

Technical documentation

www.gridgain.com/docs/index.html

docs.microsoft.com/en-us/azure/azure-sql

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

Developer

GridGain Systems, Inc.

Microsoft

Simer Plaha

Initial release

2007

2010

1989

2018

Current release

GridGain 8.5.1

V12

SQL Server 2022, November 2022

License

Commercial or Open Source

commercial, open source

commercial

restricted free version is available

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java, C++, .Net, Python, REST, SQL

C++

Scala

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

hosted

Linux
Windows

Data scheme

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

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

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

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

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

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Transact SQL

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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, with always 3 replicas available

yes, but depending on the SQL-Server Edition

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

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
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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