DBMS > Amazon DocumentDB vs. Apache Phoenix vs. ClickHouse vs. OrigoDB

System Properties Comparison Amazon DocumentDB vs. Apache Phoenix vs. ClickHouse vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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.

A fully ACID in-memory object graph database

Primary database model

Document store

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	1.91
Rank	#124	Overall
	#22	Document stores

Score	1.90
Rank	#125	Overall
	#59	Relational DBMS

Score	15.88
Rank	#37	Overall
	#22	Relational DBMS

Score	0.00
Rank	#385	Overall
	#54	Document stores
	#21	Object oriented DBMS

Website

aws.amazon.com/documentdb

phoenix.apache.org

clickhouse.com

origodb.com

Technical documentation

aws.amazon.com/documentdb/resources

phoenix.apache.org

clickhouse.com/docs

origodb.com/docs

Developer

Apache Software Foundation

Clickhouse Inc.

Robert Friberg et al

Initial release

2019

2014

2016

2009

under the name LiveDB

Current release

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

v24.6.2.17-stable, July 2024

License

Commercial or Open Source

commercial

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

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

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Implementation language

Java

C++

Server operating systems

hosted

Linux
Unix
Windows

FreeBSD
Linux
macOS

Linux
Windows

Data scheme

schema-free

yes

late-bound, schema-on-read capabilities

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC

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

.NET Client API
HTTP API
LINQ

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

key based and custom

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

Multi-source replication
Source-replica replication

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

depending on model

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

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.

Role based authorization

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