DBMS > Apache Phoenix vs. atoti vs. ClickHouse vs. EDB Postgres

System Properties Comparison Apache Phoenix vs. atoti vs. ClickHouse vs. EDB Postgres

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Editorial information provided by DB-Engines

Name

Description

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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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.

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Primary database model

Relational DBMS

Object oriented DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Website

Technical documentation

phoenix.apache.org

docs.atoti.io

clickhouse.com/docs

www.enterprisedb.com/docs

Developer

Apache Software Foundation

ActiveViam

Clickhouse Inc.

EnterpriseDB

Initial release

2014

2016

2005

Current release

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

v24.4.1.2088-stable, May 2024

14, December 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free versions available

Open Source

Apache 2.0

commercial

BSD for PostgreSQL-components

Cloud-based only

Only available as a cloud service

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

Linux
Unix
Windows

FreeBSD
Linux
macOS

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

Multidimensional Expressions (MDX)

Close to ANSI SQL (SQL/JSON + extensions)

yes

standard with numerous extensions

APIs and other access methods

JDBC

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

Python

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

key based and custom

horizontal partitioning

by hash, list or range

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

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 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.

fine grained access rights according to SQL-standard

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