DBMS > AlaSQL vs. GridGain vs. Hive vs. SpatiaLite

System Properties Comparison AlaSQL vs. GridGain vs. Hive vs. SpatiaLite

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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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Spatial extension of SQLite

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	1.63
Rank	#146	Overall
	#3	Spatial DBMS

Website

alasql.org

www.gridgain.com

hive.apache.org

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

github.com/AlaSQL/alasql

www.gridgain.com/docs/index.html

cwiki.apache.org/confluence/display/Hive/Home

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Andrey Gershun & Mathias R. Wulff

GridGain Systems, Inc.

Apache Software Foundation

initially developed by Facebook

Alessandro Furieri

Initial release

2014

2007

2012

2008

Current release

GridGain 8.5.1

3.1.3, April 2022

5.0.0, August 2020

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Java, C++, .Net

Java

C++

Server operating systems

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

Linux
OS X
Solaris
Windows

All OS with a Java VM

server-less

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

SQL-like DML and DDL statements

yes

APIs and other access methods

JavaScript API

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

JDBC
ODBC
Thrift

Supported programming languages

JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
PHP
Python

Server-side scripts

Stored procedures

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

yes

user defined functions and integration of map-reduce

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual 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

Security Hooks for custom implementations

Access rights for users, groups and roles

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More resources

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