DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Doris vs. Apache Kylin vs. ClickHouse vs. EventStoreDB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Apache Doris vs. Apache Kylin vs. ClickHouse vs. EventStoreDB

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

An MPP-based analytics DBMS embracing the MySQL protocol

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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.

Industrial-strength, open-source database solution built from the ground up for event sourcing.

Primary database model

Relational DBMS

Event Store

Secondary database models

Time Series DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.60
Rank	#247	Overall
	#113	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.19
Rank	#173	Overall
	#1	Event Stores

Website

www.alibabacloud.com/product/hybriddb-postgresql

doris.apache.org
github.com/apache/doris

kylin.apache.org

clickhouse.com

www.eventstore.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

github.com/apache/doris/wiki

kylin.apache.org/docs

clickhouse.com/docs

developers.eventstore.com

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation, originally contributed from Baidu

Apache Software Foundation, originally contributed from eBay Inc

Clickhouse Inc.

Event Store Limited

Initial release

2016

2017

2015

2016

2012

Current release

1.2.2, February 2023

3.1.0, July 2020

v24.4.1.2088-stable, May 2024

21.2, February 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux

FreeBSD
Linux
macOS

Linux
Windows

Data scheme

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

ANSI SQL for queries (using Apache Calcite)

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

C
Java
Perl
Python
R

Java

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

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning

key based and custom

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

fine grained access rights according to SQL-standard

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.

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