DBMS > Databricks vs. IBM Db2 vs. Microsoft SQL Server vs. PouchDB

System Properties Comparison Databricks vs. IBM Db2 vs. Microsoft SQL Server vs. PouchDB

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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.

Common in IBM host environments, 2 different versions for host and Windows/Linux

Microsofts flagship relational DBMS

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Document store
Relational DBMS

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

Document store

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS
Spatial DBMS

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

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

Score	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	2.34
Rank	#112	Overall
	#21	Document stores

Website

www.databricks.com

www.ibm.com/products/db2

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

pouchdb.com

Technical documentation

docs.databricks.com

www.ibm.com/docs/en/db2

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

pouchdb.com/guides

Developer

Databricks

IBM

Microsoft

Apache Software Foundation

Initial release

2013

1983

host version

1989

2012

Current release

12.1, October 2016

SQL Server 2022, November 2022

7.1.1, June 2019

License

Commercial or Open Source

commercial

free version is available

commercial

restricted free version is available

Open Source

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

C++

JavaScript

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

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

yes

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

via views

SQL

Support of SQL

with Databricks SQL

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Python
R
Scala

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

JavaScript

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

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

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

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

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

yes, but depending on the SQL-Server Edition

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

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

by using IndexedDB, WebSQL or LevelDB as backend

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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