DBMS > Apache Druid vs. FatDB vs. LokiJS vs. RDFox

System Properties Comparison Apache Druid vs. FatDB vs. LokiJS vs. RDFox

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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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

In-memory JavaScript DBMS

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Document store

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.44
Rank	#256	Overall
	#40	Document stores

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

druid.apache.org

github.com/techfort/LokiJS

www.oxfordsemantic.tech

Technical documentation

druid.apache.org/docs/latest/design

techfort.github.io/LokiJS

docs.oxfordsemantic.tech

Developer

Apache Software Foundation and contributors

FatCloud

Oxford Semantic Technologies

Initial release

2012

2014

2017

Current release

30.0.0, June 2024

6.0, Septermber 2022

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

commercial

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

Java

JavaScript

C++

Server operating systems

Linux
OS X
Unix

Windows

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

Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

RDF schemas

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

SQL

Support of SQL

SQL for querying

Via inetgration in SQL Server

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

JavaScript API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

JavaScript

C
Java

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

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

none

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

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

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Can implement custom security layer via applications

Roles, resources, and access types

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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

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