DBMS > Databricks vs. OushuDB

System Properties Comparison Databricks vs. OushuDB

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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.

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

Primary database model

Document store
Relational DBMS

Relational DBMS

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Trend Chart

Score	99.29
Rank	#12	Overall
	#2	Document stores
	#8	Relational DBMS

Score	0.00
Rank	#378	Overall
	#154	Relational DBMS

Website

www.databricks.com

www.oushu.com/product/oushuDB

Technical documentation

docs.databricks.com

www.oushu.com/documentation

Developer

Databricks

Oushu

Initial release

2013

Current release

4.0.1, August 2020

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Server operating systems

hosted

Linux

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

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

Full-featured ANSI SQL support

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Python
R
Scala

C
C++

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Kerberos, SSL and role based access

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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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Recent citations in the news

Upskill your team on Azure Databricks with an on-demand webinar and Microsoft Learn
17 April 2025, Microsoft Azure

BigQuery is 5x bigger than Snowflake and Databricks: What Google is doing to make it even better
17 April 2025, VentureBeat

Altair partners with Databricks to accelerate data-driven innovation
17 April 2025, Engineering.com

Data-driven collaboration between Altair and Databricks
17 April 2025, Automotive Testing Technology International

Altair partners with Databricks to accelerate data-driven innovation
17 April 2025, Scientific Computing World

provided by Google News

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