DBMS > Apache Druid vs. Apache Ignite vs. CrateDB

System Properties Comparison Apache Druid vs. Apache Ignite vs. CrateDB

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Editorial information provided by DB-Engines

Name

Description

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Distributed Database based on Lucene

Primary database model

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Secondary database models

Relational DBMS

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

Score	2.88
Rank	#92	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

Score	2.97
Rank	#88	Overall
	#12	Key-value stores
	#47	Relational DBMS

Score	0.66
Rank	#224	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#12	Vector DBMS

Website

druid.apache.org

ignite.apache.org

cratedb.com

Technical documentation

druid.apache.org/docs/latest/design

apacheignite.readme.io/docs

cratedb.com/docs

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Crate

Initial release

2012

2015

2013

Current release

30.0.0, June 2024

2.16.0, December 2023

5.8.1, August 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

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++, Java, .Net

Java

Server operating systems

Linux
OS X
Unix

Linux
OS X
Solaris
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Data scheme

yes

schema-less columns are supported

yes

Flexible Schema (defined schema, partial schema, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

ANSI-99 for query and DML statements, subset of DDL

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions (Javascript)

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes (replicated cache)

Configurable replication on table/partition-level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Foreign keys

Referential integrity

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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

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

Security Hooks for custom implementations

rights management via user accounts

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More resources

Recent citations in the news

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, Business Wire

Part 2: Apache Druid on Kubernetes
28 March 2024, Medium

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

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

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2025
10 December 2024, PR Newswire

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

GridGain In-Memory Data Fabric Becomes Apache Ignite
9 April 2015, Linux.com

Apache Ignite: An Overview
6 September 2023, Open Source For You

provided by Google News

CrateDB's abilities in real-time data analysis and its open schema
12 December 2024, Developer News

CrateDB Collaborates with ABB for Their industrial IoT and AI Suite
3 December 2024, The Eastern Progress Online

CrateDB Collaborates with ABB for Their industrial IoT and AI Suite
3 December 2024, WV News

Speed Up Data. Act in Real-Time.
12 December 2024, Jomfruland.net

CrateDB Appoints Jeff Olson as New CRO
9 July 2024, PR Newswire

provided by Google News

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