DBMS > Apache Druid vs. Apache Pinot vs. FatDB vs. Heroic

System Properties Comparison Apache Druid vs. Apache Pinot vs. FatDB vs. Heroic

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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

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Key-value store

Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Website

druid.apache.org

pinot.apache.org

github.com/spotify/heroic

Technical documentation

druid.apache.org/docs/latest/design

docs.pinot.apache.org

spotify.github.io/heroic

Developer

Apache Software Foundation and contributors

FatCloud

Spotify

Initial release

2012

2015

2012

2014

Current release

29.0.1, April 2024

1.0.0, September 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache Version 2.0

commercial

Open Source

Apache 2.0

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

Server operating systems

Linux
OS X
Unix

All OS with a Java JDK11 or higher

Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

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 Elasticsearch

SQL

Support of SQL

SQL for querying

SQL-like query language

Via inetgration in SQL Server

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python

Server-side scripts

Stored procedures

yes

via applications

Triggers

yes

via applications

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

yes

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

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

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

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More resources

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