DBMS > Apache Pinot vs. Oracle Coherence vs. Oracle NoSQL vs. PostgreSQL

System Properties Comparison Apache Pinot vs. Oracle Coherence vs. Oracle NoSQL vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

Oracles in-memory data grid solution

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

Primary database model

Relational DBMS

Key-value store

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.

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	0.40
Rank	#270	Overall
	#125	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

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

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Website

pinot.apache.org

www.oracle.com/java/coherence

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

www.postgresql.org

Technical documentation

docs.pinot.apache.org

docs.oracle.com/en/middleware/standalone/coherence

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

www.postgresql.org/docs

Developer

Apache Software Foundation and contributors

Oracle

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2007

2011

1989

1989: Postgres, 1996: PostgreSQL

Current release

1.0.0, September 2023

14.1, August 2023

23.3, December 2023

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

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

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Server operating systems

All OS with a Java JDK11 or higher

All OS with a Java VM

Linux
Solaris SPARC/x86

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

Data scheme

yes

schema-free

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

yes

Typing

predefined data types such as float or date

yes

optional

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-like DML and DDL statements

yes

standard with numerous extensions

APIs and other access methods

JDBC

JCache
JPA
RESTful HTTP API

RESTful HTTP API

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

Supported programming languages

Go
Java
Python

.Net
C++
Java

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

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with selectable consistency level

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

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

optionally

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

authentification to access the cache via certificates or http basic authentication

Access rights for users and roles

fine grained access rights according to SQL-standard

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