DBMS > Databricks vs. Hazelcast vs. Oracle vs. UniData,UniVerse

System Properties Comparison Databricks vs. Hazelcast vs. Oracle vs. UniData,UniVerse

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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 widely adopted in-memory data grid

Widely used RDBMS

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Multivalue DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

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	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	1286.59
Rank	#1	Overall
	#1	Relational DBMS

Score	2.25
Rank	#112	Overall
	#2	Multivalue DBMS

Website

www.databricks.com

hazelcast.com

www.oracle.com/database

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

docs.databricks.com

hazelcast.org/imdg/docs

docs.oracle.com/en/database

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Databricks

Hazelcast

Oracle

Rocket Software

Initial release

2013

2008

1980

1985

Current release

5.3.6, November 2023

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

hosted

All OS with a Java VM

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

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

schema-free

yes

Schemaless in JSON and XML columns

schema-free

Typing

predefined data types such as float or date

yes

optional

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

Python
R
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

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
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Event Listeners, Executor Services

PL/SQL

also stored procedures in Java possible

yes

Triggers

yes

Events

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

isolation level can be parameterized

ACID

configurable

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.

yes

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

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Access rights according to SQL-standard and operating system based

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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