DBMS > Oracle NoSQL vs. PostgreSQL vs. XTDB

System Properties Comparison Oracle NoSQL vs. PostgreSQL vs. XTDB

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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

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store
Relational DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	3.39
Rank	#76	Overall
	#13	Document stores
	#9	Key-value stores
	#40	Relational DBMS

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

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

www.postgresql.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.postgresql.org/docs

www.xtdb.com/docs

Developer

Oracle

PostgreSQL Global Development Group

www.postgresql.org/developer

Juxt Ltd.

Initial release

2011

1989

1989: Postgres, 1996: PostgreSQL

2019

Current release

25.1, April 2025

16.4, August 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

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

Open Source

BSD

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Clojure

Server operating systems

Linux
Solaris SPARC/x86

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

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

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

standard with numerous extensions

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

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

HTTP REST
JDBC

Supported programming languages

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

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

other methods possible by using 3rd party extensions

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Access rights for users and roles

fine grained access rights according to SQL-standard

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