DBMS > Altibase vs. ClickHouse vs. HEAVY.AI vs. KeyDB

System Properties Comparison Altibase vs. ClickHouse vs. HEAVY.AI vs. KeyDB

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

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

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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	1.00
Rank	#194	Overall
	#91	Relational DBMS

Score	16.20
Rank	#37	Overall
	#23	Relational DBMS

Score	2.10
Rank	#126	Overall
	#61	Relational DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Website

altibase.com

clickhouse.com

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

github.com/Snapchat/KeyDB
keydb.dev

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

clickhouse.com/docs

docs.heavy.ai

docs.keydb.dev

Developer

Altibase

Clickhouse Inc.

HEAVY.AI, Inc.

EQ Alpha Technology Ltd.

Initial release

1999

2016

2019

Current release

v7.3, 2023, August 2023

v23.12.1.1368-stable, December 2023

5.10, January 2022

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

BSD-3

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.
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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++

C++ and CUDA

C++

Server operating systems

AIX
HP-UX
Linux

FreeBSD
Linux
macOS

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

ANSI SQL-92

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

JDBC
ODBC
Thrift
Vega

Proprietary protocol

RESP - REdis Serialization Protoco

Supported programming languages

C
C++
Java

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

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

Sharding

Round robin

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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.

fine grained access rights according to SQL-standard

simple password-based access control and ACL

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