DBMS > Apache Doris vs. DuckDB vs. Oracle NoSQL

System Properties Comparison Apache Doris vs. DuckDB vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

An MPP-based analytics DBMS embracing the MySQL protocol

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

Primary database model

Relational DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.69
Rank	#237	Overall
	#108	Relational DBMS

Score	4.68
Rank	#76	Overall
	#41	Relational DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Website

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

duckdb.org

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

Technical documentation

github.com/apache/doris/wiki

duckdb.org/docs

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

Developer

Apache Software Foundation, originally contributed from Baidu

Oracle

Initial release

2017

2018

2011

Current release

1.2.2, February 2023

0.10, February 2024

23.3, December 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

Open Source

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

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.

Implementation language

Java

C++

Java

Server operating systems

Linux

server-less

Linux
Solaris SPARC/x86

Data scheme

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
MySQL client

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

Server-side scripts

Stored procedures

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

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

yes, multi-version concurrency control (MVCC)

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

off heap cache

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

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