DBMS > FatDB vs. HEAVY.AI vs. LokiJS vs. SpatiaLite

System Properties Comparison FatDB vs. HEAVY.AI vs. LokiJS vs. SpatiaLite

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

In-memory JavaScript DBMS

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Relational DBMS

Document store

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

github.com/heavyai/heavydb
www.heavy.ai

github.com/techfort/LokiJS

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

Technical documentation

docs.heavy.ai

techfort.github.io/LokiJS

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

Developer

FatCloud

HEAVY.AI, Inc.

Alessandro Furieri

Initial release

2012

2016

2014

2008

Current release

5.10, January 2022

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

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

C++ and CUDA

JavaScript

C++

Server operating systems

Windows

Linux

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

server-less

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.

Secondary indexes

yes

via views

yes

SQL

Support of SQL

Via inetgration in SQL Server

yes

APIs and other access methods

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
Thrift
Vega

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

Server-side scripts

Stored procedures

yes

via applications

View functions in JavaScript

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

Can implement custom security layer via applications

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

show all

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

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