DBMS > Amazon Aurora vs. Apache Drill vs. Apache Phoenix vs. ClickHouse vs. Yanza

System Properties Comparison Amazon Aurora vs. Apache Drill vs. Apache Phoenix vs. ClickHouse vs. Yanza

Editorial information provided by DB-Engines

Name

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

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

A scale-out RDBMS with evolutionary schema built on Apache HBase

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.

Time Series DBMS for IoT Applications

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Time Series DBMS

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

Score	7.91
Rank	#50	Overall
	#32	Relational DBMS

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Website

aws.amazon.com/rds/aurora

drill.apache.org

phoenix.apache.org

clickhouse.com

yanza.com

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

drill.apache.org/docs

phoenix.apache.org

clickhouse.com/docs

Developer

Amazon

Apache Software Foundation

Clickhouse Inc.

Yanza

Initial release

2015

2012

2014

2016

2015

Current release

1.20.3, January 2023

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

v24.3.2.23-lts, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Unix
Windows

FreeBSD
Linux
macOS

Windows

Data scheme

yes

schema-free

yes

late-bound, schema-on-read capabilities

yes

schema-free

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

SQL SELECT statement is SQL:2003 compliant

yes

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC

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

HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

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

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

key based and custom

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication
Source-replica replication

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency or Eventual Consistency

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

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on the underlying data source

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Depending on the underlying data source

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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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