DBMS > Databricks vs. DuckDB vs. Oracle

System Properties Comparison Databricks vs. DuckDB vs. Oracle

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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.

An embeddable, in-process, column-oriented SQL OLAP RDBMS

Widely used RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	4.57
Rank	#74	Overall
	#40	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

www.databricks.com

duckdb.org

www.oracle.com/database

Technical documentation

docs.databricks.com

duckdb.org/docs

docs.oracle.com/en/database

Developer

Databricks

Oracle

Initial release

2013

2018

1980

Current release

0.10, February 2024

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

C and C++

Server operating systems

hosted

server-less

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

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

yes

Schemaless in JSON and XML columns

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

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Python
R
Scala

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions and aggregates

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

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

isolation level can be parameterized

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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.

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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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