DBMS > ClickHouse vs. jBASE vs. RisingWave vs. ToroDB

System Properties Comparison ClickHouse vs. jBASE vs. RisingWave vs. ToroDB

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Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

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.

A robust multi-value DBMS comprising development tools and middleware

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

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

clickhouse.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

www.risingwave.com/database

github.com/torodb/server

Technical documentation

clickhouse.com/docs

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

docs.risingwave.com/docs/current/intro

Developer

Clickhouse Inc.

Rocket Software (formerly Zumasys)

RisingWave Labs

8Kdata

Initial release

2016

1991

2022

2016

Current release

v24.4.1.2088-stable, May 2024

5.7

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2.0

Open Source

AGPL-V3

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.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

Rust

Java

Server operating systems

FreeBSD
Linux
macOS

AIX
Linux
Windows

Docker
Linux
macOS

All OS with a Java 7 VM

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

Standard SQL-types and JSON

yes

string, integer, double, boolean, date, object_id

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.

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Embedded SQL for jBASE in BASIC

yes

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based 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

.Net
Basic
Jabbascript
Java

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

UDFs in Python or Java

Triggers

yes

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.

yes

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
Immediate Consistency

Foreign keys

Referential integrity

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 can be defined down to the item level

Users and Roles

Access rights for users and roles

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