DBMS > ClickHouse vs. Memcached vs. Microsoft Azure AI Search vs. StarRocks

System Properties Comparison ClickHouse vs. Memcached vs. Microsoft Azure AI Search vs. StarRocks

Please select another system to include it in the comparison.

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.

In-memory key-value store, originally intended for caching

Search-as-a-service for web and mobile app development

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

Forked from Apache Doris

Primary database model

Secondary database models

Time Series DBMS

Vector DBMS

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

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	16.84
Rank	#32	Overall
	#4	Key-value stores

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Website

clickhouse.com

www.memcached.org

azure.microsoft.com/en-us/services/search

www.starrocks.io

Technical documentation

clickhouse.com/docs

github.com/memcached/memcached/wiki

learn.microsoft.com/en-us/azure/search

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

Developer

Clickhouse Inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

The Linux Foundation

since Feb 2023

Initial release

2016

2003

2015

2020

Current release

v24.6.2.17-stable, July 2024

1.6.29, June 2024

3.3, June 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD license

commercial

Open Source

Apache Version 2.0

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.

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.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

C++

C++, Java

Server operating systems

FreeBSD
Linux
macOS

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

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

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

Proprietary protocol

RESTful HTTP API

JDBC
MySQL 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
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

Sharding

Implicit feature of the cloud service

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

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.

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

using Azure authentication

Role based access control and fine grained access rights

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.