DBMS > Apache Doris vs. Citus vs. Oracle NoSQL vs. PouchDB

System Properties Comparison Apache Doris vs. Citus vs. Oracle NoSQL vs. PouchDB

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

Document store

Secondary database models

Document store

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

Score	0.61
Rank	#235	Overall
	#110	Relational DBMS

Score	2.13
Rank	#117	Overall
	#56	Relational DBMS

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	2.18
Rank	#114	Overall
	#21	Document stores

Website

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

www.citusdata.com

www.oracle.com/database/nosql/technologies/nosql

pouchdb.com

Technical documentation

github.com/apache/doris/wiki

docs.citusdata.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

pouchdb.com/guides

Developer

Apache Software Foundation, originally contributed from Baidu

Oracle

Apache Software Foundation

Initial release

2017

2010

2011

2012

Current release

1.2.2, February 2023

8.1, December 2018

24.1, May 2024

7.1.1, June 2019

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL, commercial license also available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

JavaScript

Server operating systems

Linux

Linux
Solaris SPARC/x86

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

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

via views

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC
MySQL client

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

RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
Go
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions

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

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

In-memory capabilities

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

yes

off heap cache

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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Recent citations in the news

Breaking Down Data Silos: How Apache Doris Streamlines Customer Data Integration
20 March 2024, hackernoon.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Migrating from ClickHouse to Apache Doris: Boosting OLAP Performance
9 October 2023, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Apache Doris Analytical Database Graduates from Apache Incubator
20 June 2022, Datanami

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24 January 2019, blogs.microsoft.com

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5 March 2024, TechCrunch

Microsoft acquires Citus Data, creators of a cloud-friendly version of the PostgreSQL database
24 January 2019, GeekWire

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24 January 2019, Business Insider

Microsoft acquires another open-source company, Citus Data
24 January 2019, CNBC

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