DBMS > AlaSQL vs. GridGain vs. Microsoft Azure SQL Database vs. Transwarp KunDB

System Properties Comparison AlaSQL vs. GridGain vs. Microsoft Azure SQL Database vs. Transwarp KunDB

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Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Document store
Relational DBMS

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.42
Rank	#264	Overall
	#42	Document stores
	#122	Relational DBMS

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	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

alasql.org

www.gridgain.com

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

www.transwarp.cn/en/product/kundb

Technical documentation

github.com/AlaSQL/alasql

www.gridgain.com/docs/index.html

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

Developer

Andrey Gershun & Mathias R. Wulff

GridGain Systems, Inc.

Microsoft

Transwarp

Initial release

2014

2007

2010

Current release

GridGain 8.5.1

V12

License

Commercial or Open Source

Open Source

MIT-License

commercial, open source

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

JavaScript

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

C++

Server operating systems

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Solaris
Windows
z/OS

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

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

yes

APIs and other access methods

JavaScript API

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

ADO.NET
JDBC
ODBC

Supported programming languages

JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

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

Server-side scripts

Stored procedures

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

Transact SQL

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes, with always 3 replicas available

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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

yes

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