DBMS > Databricks vs. Netezza vs. PostgreSQL

System Properties Comparison Databricks vs. Netezza vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Data warehouse and analytics appliance part of IBM PureSystems

Widely used open source RDBMS

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

Primary database model

Document 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	83.29
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	8.15
Rank	#46	Overall
	#30	Relational DBMS

Score	638.91
Rank	#4	Overall
	#4	Relational DBMS

Website

www.databricks.com

www.ibm.com/products/netezza

www.postgresql.org

Technical documentation

docs.databricks.com

www.postgresql.org/docs

Developer

Databricks

IBM

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2013

2000

1989

1989: Postgres, 1996: PostgreSQL

Current release

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

hosted

Linux

included in appliance

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

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

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

with Databricks SQL

yes

standard with numerous extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
OLE DB

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

Supported programming languages

Python
R
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

User concepts

Access control

Users with fine-grained authorization concept

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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Related products and services

3rd parties

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Navicat Monitor is a safe, simple and agentless remote server monitoring tool for PostgreSQL and many other database management systems.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

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2 January 2024, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2022, defending the title from last year
3 January 2023, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2021
3 January 2022, Paul Andlinger, Matthias Gelbmann

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Conferences, events and webinars

more DBMS events

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

Recent citations in the news

The People in Charge at Databricks as It Moves Toward a Potential IPO
24 July 2024, The Information

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provided by Google News

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21 June 2024, IBM

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31 May 2024, Data Center Knowledge

Sorting out Netezza and Oracle Exadata Data Warehouse Appliance Pricing
30 October 2023, InformationWeek

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift
27 May 2020, AWS Blog

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Synopsis of several compelling features in PostgreSQL 16 | Amazon Web Services
12 July 2024, AWS Blog

Pgextensions Index For PostgreSQL
22 July 2024, iProgrammer

Best of Makers: PostgreSQL Takes a New Turn
22 February 2024, The New Stack

General availability: Azure Database for PostgreSQL - Flexible Server enhanced disaster recovery features
24 April 2024, Microsoft

Managed PostgreSQL service provider Tembo raises $14M
3 July 2024, SiliconANGLE News

provided by Google News

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