DBMS > AlaSQL vs. GridGain vs. Microsoft SQL Server vs. PouchDB vs. WakandaDB

System Properties Comparison AlaSQL vs. GridGain vs. Microsoft SQL Server vs. PouchDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

alasql.org

www.gridgain.com

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

pouchdb.com

wakanda.github.io

Technical documentation

github.com/AlaSQL/alasql

www.gridgain.com/docs/index.html

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

pouchdb.com/guides

wakanda.github.io/doc

Developer

Andrey Gershun & Mathias R. Wulff

GridGain Systems, Inc.

Microsoft

Apache Software Foundation

Wakanda SAS

Initial release

2014

2007

1989

2012

Current release

GridGain 8.5.1

SQL Server 2022, November 2022

7.1.1, June 2019

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

MIT-License

commercial

restricted free version is available

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java, C++, .Net

C++

JavaScript

C++, JavaScript

Server operating systems

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

Linux
OS X
Solaris
Windows

Linux
Windows

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

Linux
OS X
Windows

Data scheme

schema-free

yes

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

via views

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
OLE DB
Tabular Data Stream (TDS)

HTTP REST

only for PouchDB Server
JavaScript API

RESTful HTTP API

Supported programming languages

JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

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

JavaScript

Server-side scripts

Stored procedures

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

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

View functions in JavaScript

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

Sharding

with a proxy-based framework, named couchdb-lounge

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

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

by using IndexedDB, WebSQL or LevelDB as backend

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

yes

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