DBMS > ClickHouse vs. ReductStore vs. RisingWave

System Properties Comparison ClickHouse vs. ReductStore vs. RisingWave

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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.

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

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

Score	18.61
Rank	#31	Overall
	#19	Relational DBMS

Score	0.07
Rank	#354	Overall
	#37	Time Series DBMS

Score	0.64
Rank	#226	Overall
	#104	Relational DBMS

Website

clickhouse.com

github.com/reductstore
www.reduct.store

www.risingwave.com/database

Technical documentation

clickhouse.com/docs

www.reduct.store/docs

docs.risingwave.com/docs/current/intro

Developer

Clickhouse Inc.

ReductStore LLC

RisingWave Labs

Initial release

2016

2023

2022

Current release

v24.6.2.17-stable, July 2024

1.9, March 2024

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Business Source License 1.1

Open Source

Apache Version 2.0

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.

Implementation language

C++

C++, Rust

Rust

Server operating systems

FreeBSD
Linux
macOS

Docker
Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

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

HTTP API

JDBC
PostgreSQL wire protocol

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++
JavaScript (Node.js)
Python
Rust

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Replication methods

Methods for redundantly storing data on multiple nodes

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

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. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Users and Roles

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