DBMS > BigObject vs. Databricks vs. Microsoft SQL Server vs. Oracle Rdb

System Properties Comparison BigObject vs. Databricks vs. Microsoft SQL Server vs. Oracle Rdb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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.

Microsofts flagship relational DBMS

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

bigobject.io

www.databricks.com

www.microsoft.com/en-us/sql-server

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

docs.bigobject.io

docs.databricks.com

learn.microsoft.com/en-US/sql/sql-server

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

BigObject, Inc.

Databricks

Microsoft

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2015

2013

1989

1984

Current release

SQL Server 2022, November 2022

7.4.1.1, 2021

License

Commercial or Open Source

commercial

free community edition 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

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

hosted

Linux
Windows

HP Open VMS

Data scheme

yes

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

yes

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

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

SQL-like DML and DDL statements

with Databricks SQL

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Python
R
Scala

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

Lua

user defined functions and aggregates

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

yes, on a single node

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

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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