DBMS > ClickHouse vs. StarRocks vs. STSdb vs. Vertica vs. YugabyteDB

System Properties Comparison ClickHouse vs. StarRocks vs. STSdb vs. Vertica vs. YugabyteDB

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, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Column oriented

Secondary database models

Time Series DBMS

Spatial DBMS
Time Series DBMS

Document store
Wide column store

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Score	2.48
Rank	#108	Overall
	#53	Relational DBMS

Website

clickhouse.com

www.starrocks.io

github.com/STSSoft/STSdb4

www.vertica.com

www.yugabyte.com

Technical documentation

clickhouse.com/docs

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

vertica.com/documentation

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

Clickhouse Inc.

The Linux Foundation

since Feb 2023

STS Soft SC

OpenText

previously Micro Focus and Hewlett Packard

Yugabyte Inc.

Initial release

2016

2020

2011

2005

2017

Current release

v24.6.2.17-stable, July 2024

3.3, June 2024

4.0.8, September 2015

12.0.3, January 2023

2.19, September 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

GPLv2, commercial license available

commercial

Limited community edition free

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

C++

C++, Java

C++

C and C++

Server operating systems

FreeBSD
Linux
macOS

Linux

Windows

Linux

Linux
OS X

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

depending on used data model

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

yes, PostgreSQL compatible

APIs and other access methods

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

JDBC
MySQL protocol

.NET Client API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

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

Java

C#
Java

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

user defined functions

yes, PostgreSQL PL/pgSQL, with minor differences

yes

sql, plpgsql, C

Triggers

yes, called Custom Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

horizontal partitioning (by range and hash)

none

horizontal partitioning, hierarchical partitioning

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

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.

Role based access control and fine grained access rights

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

yes

More information provided by the system vendor

Specific characteristics

YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

Systems of record and engagement for cloud native applications that require resilience,...
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Market metrics

2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

Apache 2.0 license for the database
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