DBMS > Databricks vs. FoundationDB vs. GeoSpock vs. Oracle vs. OrigoDB

System Properties Comparison Databricks vs. FoundationDB vs. GeoSpock vs. Oracle vs. OrigoDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

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.

Ordered key-value store. Core features are complimented by layers.

Spatial and temporal data processing engine for extreme data scale

Widely used RDBMS

A fully ACID in-memory object graph database

Primary database model

Document store
Relational DBMS

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

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	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

www.databricks.com

github.com/apple/foundationdb

geospock.com

www.oracle.com/database

origodb.com

Technical documentation

docs.databricks.com

apple.github.io/foundationdb

docs.oracle.com/en/database

origodb.com/docs

Developer

Databricks

FoundationDB

GeoSpock

Oracle

Robert Friberg et al

Initial release

2013

1980

2009

under the name LiveDB

Current release

6.2.28, November 2020

2.0, September 2019

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java, Javascript

C and C++

Server operating systems

hosted

Linux
OS X
Windows

hosted

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

Linux
Windows

Data scheme

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

schema-free

some layers support schemas

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

some layers support typing

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

with Databricks SQL

supported in specific SQL layer only

ANSI SQL for query only (using Presto)

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
HTTP API
LINQ

Supported programming languages

Python
R
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

in SQL-layer only

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Automatic sharding

Sharding, horizontal partitioning

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica 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

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

depending on model

Transaction concepts

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

ACID

isolation level can be parameterized

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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'

yes

User concepts

Access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

Role based authorization

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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