DBMS > ClickHouse vs. Immudb vs. Snowflake vs. SQream DB vs. Transwarp StellarDB

System Properties Comparison ClickHouse vs. Immudb vs. Snowflake vs. SQream DB vs. Transwarp StellarDB

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.

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

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

a GPU-based, columnar RDBMS for big data analytics workloads

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.24
Rank	#295	Overall
	#42	Key-value stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

clickhouse.com

github.com/codenotary/immudb
immudb.io

www.snowflake.com

sqream.com

www.transwarp.cn/en/product/stellardb

Technical documentation

clickhouse.com/docs

docs.immudb.io

docs.snowflake.net/manuals/index.html

docs.sqream.com

Developer

Clickhouse Inc.

Codenotary

Snowflake Computing Inc.

SQream Technologies

Transwarp

Initial release

2016

2020

2014

2017

Current release

v24.6.2.17-stable, July 2024

1.2.3, April 2022

2022.1.6, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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.

Implementation language

C++

C++, CUDA, Haskell, Java, Scala

Server operating systems

FreeBSD
Linux
macOS

BSD
Linux
macOS
Solaris
Windows
z/OS

hosted

Linux

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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)

SQL-like syntax

yes

SQL-like query language

APIs and other access methods

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

gRPC protocol
PostgreSQL wire protocol

CLI Client
JDBC
ODBC

.Net
JDBC
ODBC

OpenCypher

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
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

user defined functions in Python

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

yes

horizontal and vertical partitioning

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

none

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

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.

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

yes

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