DBMS > ClickHouse vs. Kinetica vs. Riak TS vs. Sequoiadb

System Properties Comparison ClickHouse vs. Kinetica vs. Riak TS vs. Sequoiadb

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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.

Fully vectorized database across both GPUs and CPUs

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

Time Series DBMS

Document store
Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	0.42
Rank	#263	Overall
	#41	Document stores
	#121	Relational DBMS

Website

clickhouse.com

www.kinetica.com

www.sequoiadb.com

Technical documentation

clickhouse.com/docs

docs.kinetica.com

www.tiot.jp/riak-docs/riak/ts/latest

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Clickhouse Inc.

Kinetica

Open Source, formerly Basho Technologies

Sequoiadb Ltd.

Initial release

2016

2012

2015

2013

Current release

v24.6.2.17-stable, July 2024

7.1, August 2021

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Server: AGPL; Client: Apache V2

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.

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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

C, C++

Erlang

C++

Server operating systems

FreeBSD
Linux
macOS

Linux

Linux
OS X

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

restricted

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like DML and DDL statements

yes, limited

SQL-like query language

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

proprietary protocol using JSON

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
JavaScript (Node.js)
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

Erlang

JavaScript

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

Document is locked during a transaction

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

GPU vRAM or System RAM

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.

Access rights for users and roles on table level

simple password-based access control

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