DBMS > Oracle NoSQL vs. RethinkDB vs. Vitess

System Properties Comparison Oracle NoSQL vs. RethinkDB vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store
Key-value store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Spatial DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

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

rethinkdb.com

vitess.io

Technical documentation

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

rethinkdb.com/docs

vitess.io/docs

Developer

Oracle

The Linux Foundation

since July 2017

The Linux Foundation, PlanetScale

Initial release

2011

2009

2013

Current release

23.3, December 2023

2.4.1, August 2020

15.0.2, December 2022

License

Commercial or Open Source

Open Source

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

Open Source

Apache Version 2

Open Source

Apache Version 2.0, commercial licenses available

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++

Server operating systems

Linux
Solaris SPARC/x86

Linux
OS X
Windows

Docker
Linux
macOS

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

string, binary, float, bool, date, geometry

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

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

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

configurable

ACID within a storage node (=shard)

Atomic single-document operations

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

table locks or row locks depending on storage engine

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

yes

User concepts

Access control

Access rights for users and roles

yes

users and table-level permissions

Users with fine-grained authorization concept

no user groups or roles

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More resources

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