DBMS > ClickHouse vs. HEAVY.AI vs. STSdb

System Properties Comparison ClickHouse vs. HEAVY.AI vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Column-oriented Relational DBMS powering Yandex

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	16.96
Rank	#39	Overall
	#24	Relational DBMS

Score	3.01
Rank	#111	Overall
	#55	Relational DBMS

Score	0.35
Rank	#317	Overall
	#45	Key-value stores

Website

clickhouse.com

github.com/heavyai/heavydb
www.heavy.ai

github.com/STSSoft/STSdb4

Technical documentation

clickhouse.com/docs

docs.heavy.ai

Developer

Clickhouse Inc.

HEAVY.AI, Inc.

STS Soft SC

Initial release

2016

2011

Current release

v23.7.4.5-stable, August 2023

5.10, January 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

GPLv2, 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.

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

Implementation language

C++

C++ and CUDA

Server operating systems

FreeBSD
Linux
macOS

Linux

Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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, when using the MergeTree engine

SQL

Support of SQL

Close to ANSI SQL

yes

APIs and other access methods

HTTP REST
JDBC
ODBC
Proprietary protocol

JDBC
ODBC
Thrift
Vega

.NET Client 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
Scala

3rd party library

All languages supporting JDBC/ODBC/Thrift
Python

C#
Java

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

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

fine grained access rights according to SQL-standard

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