DBMS > ClickHouse vs. Riak TS vs. Rockset vs. Snowflake

System Properties Comparison ClickHouse vs. Riak TS vs. Rockset vs. Snowflake

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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.

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

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS
Search engine

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

clickhouse.com

rockset.com

www.snowflake.com

Technical documentation

clickhouse.com/docs

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

docs.rockset.com

docs.snowflake.net/manuals/index.html

Developer

Clickhouse Inc.

Open Source, formerly Basho Technologies

Rockset

Snowflake Computing Inc.

Initial release

2016

2015

2019

2014

Current release

v24.4.2.141-stable, June 2024

3.0.0, September 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

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

Implementation language

C++

Erlang

C++

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

yes

restricted

all fields are automatically indexed

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes, limited

Read-only SQL queries, including JOINs

yes

APIs and other access methods

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

HTTP API
Native Erlang Interface

HTTP REST

CLI Client
JDBC
ODBC

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

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

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Erlang

user defined functions

Triggers

yes

pre-commit hooks and post-commit hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Automatic sharding

yes

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

links between datasets can be stored

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.

Access rights for users and organizations can be defined via Rockset console

Users with fine-grained authorization concept, user roles and pluggable authentication

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