DBMS > Oracle NoSQL vs. Postgres-XL vs. RethinkDB vs. SQLite

System Properties Comparison Oracle NoSQL vs. Postgres-XL vs. RethinkDB vs. SQLite

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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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	2.66
Rank	#107	Overall
	#20	Document stores

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

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

www.postgres-xl.org

rethinkdb.com

www.sqlite.org

Technical documentation

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

www.postgres-xl.org/documentation

rethinkdb.com/docs

www.sqlite.org/docs.html

Developer

Oracle

The Linux Foundation

since July 2017

Dwayne Richard Hipp

Initial release

2011

2014

since 2012, originally named StormDB

2009

2000

Current release

24.1, May 2024

10 R1, October 2018

2.4.1, August 2020

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

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

Open Source

Mozilla public license

Open Source

Apache Version 2

Open Source

Public Domain

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
macOS

Linux
OS X
Windows

server-less

Data scheme

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

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

optional

yes

string, binary, float, bool, date, geometry

yes

not rigid because of 'dynamic typing' concept.

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

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

distributed, parallel query execution

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

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

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

range based

none

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

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

MVCC

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

via file-system locks

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

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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