DBMS > Apache Cassandra vs. Apache Druid vs. DataFS vs. SiriDB

System Properties Comparison Apache Cassandra vs. Apache Druid vs. DataFS vs. SiriDB

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Open Source Time Series DBMS

Primary database model

Wide column store

Relational DBMS
Time Series DBMS

Object oriented DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

Graph DBMS

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

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

Technical documentation

cassandra.apache.org/doc/latest

druid.apache.org/docs/latest/design

dev.mobiland.com/Overview.xsp

docs.siridb.com

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation and contributors

Mobiland AG

Cesbit

Initial release

2008

2012

2018

2017

Current release

5.0-rc1, July 2024

30.0.0, June 2024

1.1.263, October 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache license v2

commercial

Open Source

MIT License

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Unix

Windows

Linux

Data scheme

schema-free

yes

schema-less columns are supported

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

SQL-like SELECT, DML and DDL statements (CQL)

SQL for querying

APIs and other access methods

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

JDBC
RESTful HTTP/JSON API

.NET Client API
Proprietary client DLL
WinRT client

HTTP API

Supported programming languages

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C#
C++
VB.Net

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

Triggers

yes

no, except callback-events from server when changes happened

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

manual/auto, time-based

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Representation of geographical distribution of servers is possible

yes, via HDFS, S3 or other storage engines

yes

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

can be individually decided for each write operation

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomicity and isolation are supported for single operations

ACID

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.

yes

User concepts

Access control

Access rights for users can be defined per object

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

Windows-Profile

simple rights management via user accounts

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
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Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
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Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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