DBMS > Apache Druid vs. FatDB vs. Hawkular Metrics vs. PouchDB vs. Snowflake

System Properties Comparison Apache Druid vs. FatDB vs. Hawkular Metrics vs. PouchDB vs. Snowflake

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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

JavaScript DBMS with an API inspired by CouchDB

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS
Time Series DBMS

Document store
Key-value store

Time Series DBMS

Document store

Relational 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	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

Technical documentation

druid.apache.org/docs/latest/design

www.hawkular.org/hawkular-metrics/docs/user-guide

pouchdb.com/guides

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

FatCloud

Community supported by Red Hat

Apache Software Foundation

Snowflake Computing Inc.

Initial release

2012

2014

2012

2014

Current release

29.0.1, April 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

Linux
OS X
Unix

Windows

Linux
OS X
Windows

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

hosted

Data scheme

yes

schema-less columns are supported

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL for querying

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

HTTP REST

only for PouchDB Server
JavaScript API

CLI Client
JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Java
Python
Ruby

JavaScript

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

via applications

View functions in JavaScript

user defined functions

Triggers

yes

via applications

yes

via Hawkular Alerting

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

based on Cassandra

Sharding

with a proxy-based framework, named couchdb-lounge

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

based on Cassandra

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

Can implement custom security layer via applications

Users with fine-grained authorization concept, user roles and pluggable authentication

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