DBMS > Apache Druid vs. ClickHouse vs. CrateDB vs. Datastax Enterprise

System Properties Comparison Apache Druid vs. ClickHouse vs. CrateDB vs. Datastax Enterprise

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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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Distributed Database based on Lucene

DataStax Enterprise (DSE) is the always-on, scalable data platform built on Apache Cassandra and designed for hybrid Cloud. DSE integrates graph, search, analytics, administration, developer tooling, and monitoring into a unified platform.

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Wide column store

Secondary database models

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Spatial DBMS
Search engine
Vector 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	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	5.93
Rank	#56	Overall
	#4	Wide column stores

Website

druid.apache.org

clickhouse.com

cratedb.com

www.datastax.com/products/datastax-enterprise

Technical documentation

druid.apache.org/docs/latest/design

clickhouse.com/docs

cratedb.com/docs

docs.datastax.com

Developer

Apache Software Foundation and contributors

Clickhouse Inc.

Crate

DataStax

Initial release

2012

2016

2013

2011

Current release

29.0.1, April 2024

v24.4.2.141-stable, June 2024

6.8, April 2020

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

commercial

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.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.

CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.

Datastax Astra DB: Astra DB simplifies cloud-native Cassandra application development for your apps, microservices and functions. Deploy in minutes on AWS, Google Cloud, Azure, and have it managed for you by the experts, with serverless, pay-as-you-go pricing.

Implementation language

Java

C++

Java

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
macOS

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X

Data scheme

yes

schema-less columns are supported

yes

Flexible Schema (defined schema, partial schema, schema free)

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

SQL

Support of SQL

SQL for querying

Close to ANSI SQL (SQL/JSON + extensions)

yes, but no triggers and constraints, and PostgreSQL compatibility

SQL-like DML and DDL statements (CQL); Spark SQL

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

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

Proprietary protocol

CQL (Cassandra Query Language)
TinkerPop Gremlin

with DSE Graph

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

.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

C
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions (Javascript)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

key based and custom

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

Configurable replication on table/partition-level

configurable replication factor, datacenter aware, advanced replication for edge computing

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
Read-after-write consistency on record level

Immediate Consistency
Tunable Consistency

consistency level can be individually decided with each write operation

Foreign keys

Referential integrity

Transaction concepts

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

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

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.

yes

User concepts

Access control

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

rights management via user accounts

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

The enterprise database for time series, documents, and vectors. Distributed - Native...
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DataStax Enterprise is scale-out data infrastructure for enterprises that need to...
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Competitive advantages

Response time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more

Supporting the following application requirements: Zero downtime - Built on Apache...
» more

Typical application scenarios

IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more

Applications that must be massively and linearly scalable with 100% uptime and able...
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Key customers

Across all continents, CrateDB is used by companies of all sizes to meet the most...
» more

Capital One, Cisco, Comcast, eBay, McDonald's, Microsoft, Safeway, Sony, UBS, and...
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Market metrics

The CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
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Among the Forbes 100 Most Innovative Companies, DataStax is trusted by 5 of the top...
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Licensing and pricing models

See CrateDB pricing >
» more

Annual subscription
» more

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