DBMS > Apache Cassandra vs. Apache Druid vs. IRONdb

System Properties Comparison Apache Cassandra vs. Apache Druid vs. IRONdb

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Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Primary database model

Wide column store

Relational DBMS
Time Series DBMS

Time Series DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	106.65
Rank	#11	Overall
	#1	Wide column stores

Score	2.79
Rank	#89	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Website

cassandra.apache.org

druid.apache.org

www.circonus.com/solutions/time-series-database/

Technical documentation

cassandra.apache.org/doc/latest

druid.apache.org/docs/latest/design

docs.circonus.com/irondb/category/getting-started

Developer

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation and contributors

Circonus LLC.

Initial release

2008

2012

2017

Current release

5.0-rc1, July 2024

30.0.0, June 2024

V0.10.20, January 2018

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Apache license v2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

BSD
Linux
OS X
Windows

Linux
OS X
Unix

Linux

Data scheme

schema-free

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL-like query language (Circonus Analytics Query Language: CAQL)

APIs and other access methods

Proprietary protocol

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

JDBC
RESTful HTTP/JSON API

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++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes, in Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

manual/auto, time-based

Automatic, metric affinity per node

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

configurable replication factor, datacenter aware

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

Immediate consistency per node, eventual consistency across nodes

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

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

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

More information provided by the system vendor

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More resources

Recent citations in the news

Best practices for running Apache Cassandra with Amazon EBS
8 November 2024, AWS Blog

IBM plans to buy open source Cassandra wrangler DataStax
25 February 2025, The Register

IBM to buy Cassandra specialist DataStax
25 February 2025, The Stack

New Apache Cassandra 5.0 gives open source NoSQL database a scalability and performance boost
6 September 2024, VentureBeat

Apache Cassandra survey highlights growing adoption for AI workloads
11 November 2024, Blocks and Files

provided by Google News

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26 June 2024, Business Wire

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18 October 2021, Towards Data Science

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

Imply advances Apache Druid real-time analytics database
20 September 2022, TechTarget

Apache Druid 25.0 Delivers Multi-Stage Query Engine and Kubernetes Task Management
19 January 2023, InfoQ.com

provided by Google News

Apica gets $6 million in funding and buys Circonus -
21 February 2024, Enterprise Times

provided by Google News

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