DBMS > ClickHouse vs. CrateDB vs. WakandaDB

System Properties Comparison ClickHouse vs. CrateDB vs. WakandaDB

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Editorial information provided by DB-Engines

Name

Description

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

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Object oriented DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	18.56
Rank	#30	Overall
	#18	Relational DBMS

Score	0.64
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#17	Search engines
	#19	Time Series DBMS
	#14	Vector DBMS

Score	0.03
Rank	#359	Overall
	#17	Object oriented DBMS

Website

clickhouse.com

cratedb.com

wakanda.github.io

Technical documentation

clickhouse.com/docs

cratedb.com/docs

wakanda.github.io/doc

Developer

Clickhouse Inc.

Crate

Wakanda SAS

Initial release

2016

2013

2012

Current release

v24.6.2.17-stable, July 2024

5.8.1, August 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPLv3, extended commercial license available

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.

Implementation language

C++

Java

C++, JavaScript

Server operating systems

FreeBSD
Linux
macOS

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

Linux
OS X
Windows

Data scheme

yes

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

yes

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

Close to ANSI SQL (SQL/JSON + extensions)

yes, but no triggers and constraints, and PostgreSQL compatibility

APIs and other access methods

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

RESTful HTTP API

Supported programming languages

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

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions (Javascript)

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Configurable replication on table/partition-level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

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

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 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

yes

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More resources

Recent citations in the news

A Beginner’s Guide to ClickHouse Database
13 September 2024, KDnuggets

ClickHouse Announces Strategic Collaboration Agreement with AWS to Advance Real-Time Data Analytics and Generative AI Innovation
10 December 2024, Business Wire

Azur Games migrates all game analytics data to ClickHouse Cloud on AWS
16 July 2024, AWS Blog

Real-time database startup ClickHouse acquires PeerDB to expand its Postgres support
30 July 2024, TechCrunch

Database startup ClickHouse Announces PeerDB Acquistion
31 July 2024, Tech Times

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, PR Newswire

Crate.io raises $10M to grow its database platform
15 June 2021, VentureBeat

CrateDB 4.5 takes distributed SQL database open source
24 March 2021, TechTarget

Real-Time Analytics Database Company CrateDB Names Lars Färnström as New CEO
1 March 2023, Business Wire

provided by Google News

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