DBMS > ClickHouse vs. FatDB vs. Hive vs. Microsoft Azure SQL Database vs. WakandaDB

System Properties Comparison ClickHouse vs. FatDB vs. Hive vs. Microsoft Azure SQL Database vs. WakandaDB

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

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.

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Database as a Service offering with high compatibility to Microsoft SQL Server

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
Key-value store

Relational DBMS

Object oriented DBMS

Secondary database models

Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

clickhouse.com

hive.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

wakanda.github.io

Technical documentation

clickhouse.com/docs

cwiki.apache.org/confluence/display/Hive/Home

docs.microsoft.com/en-us/azure/azure-sql

wakanda.github.io/doc

Developer

Clickhouse Inc.

FatCloud

Apache Software Foundation

initially developed by Facebook

Microsoft

Wakanda SAS

Initial release

2016

2012

2010

2012

Current release

v24.4.1.2088-stable, May 2024

3.1.3, April 2022

V12

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

commercial

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
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.

Implementation language

C++

Java

C++

C++, JavaScript

Server operating systems

FreeBSD
Linux
macOS

Windows

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

yes

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Via inetgration in SQL Server

SQL-like DML and DDL statements

yes

APIs and other access methods

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

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
ODBC
Thrift

ADO.NET
JDBC
ODBC

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

C++
Java
PHP
Python

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

JavaScript

Server-side scripts

Stored procedures

yes

via applications

yes

user defined functions and integration of map-reduce

Transact SQL

yes

Triggers

yes

via applications

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.

selectable replication factor

yes, with always 3 replicas available

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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.

Can implement custom security layer via applications

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

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