DBMS > Databricks vs. PouchDB vs. Splunk vs. STSdb vs. Transbase

System Properties Comparison Databricks vs. PouchDB vs. Splunk vs. STSdb vs. Transbase

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.

JavaScript DBMS with an API inspired by CouchDB

Analytics Platform for Big Data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store
Relational DBMS

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	2.28
Rank	#115	Overall
	#21	Document stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.databricks.com

pouchdb.com

www.splunk.com

github.com/STSSoft/STSdb4

www.transaction.de/en/products/transbase.html

Technical documentation

docs.databricks.com

pouchdb.com/guides

docs.splunk.com/Documentation/Splunk

www.transaction.de/en/products/transbase/features.html

Developer

Databricks

Apache Software Foundation

Splunk Inc.

STS Soft SC

Transaction Software GmbH

Initial release

2013

2012

2003

2011

1987

Current release

7.1.1, June 2019

4.0.8, September 2015

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

commercial

Limited free edition and free developer edition available

Open Source

GPLv2, commercial license available

commercial

free development license

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

JavaScript

C and C++

Server operating systems

hosted

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

Linux
OS X
Solaris
Windows

Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

yes

SQL

Support of SQL

with Databricks SQL

Splunk Search Processing Language for search commands

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST

.NET Client API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Python
R
Scala

JavaScript

C#
Java
JavaScript
PHP
Python
Ruby

C#
Java

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Multi-source replication

none

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

Access rights for users and roles

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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Recent citations in the news

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21 May 2024, Fortune

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22 May 2024, CXOToday.com

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7 September 2016, SitePoint

3 Reasons To Think Offline First
22 March 2017, IBM

Create Offline Web Apps Using Service Workers & PouchDB — SitePoint
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Offline-first web and mobile apps: Top frameworks and components
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