DBMS > Databricks vs. MySQL vs. PouchDB vs. RocksDB vs. Transbase

System Properties Comparison Databricks vs. MySQL vs. PouchDB vs. RocksDB 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.

Widely used open source RDBMS

JavaScript DBMS with an API inspired by CouchDB

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Document store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Document store

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial 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	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

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

Technical documentation

docs.databricks.com

dev.mysql.com/doc

pouchdb.com/guides

github.com/facebook/rocksdb/wiki

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

Developer

Databricks

Oracle

since 2010, originally MySQL AB, then Sun

Apache Software Foundation

Facebook, Inc.

Transaction Software GmbH

Initial release

2013

1995

2012

2013

1987

Current release

8.4.0, April 2024

7.1.1, June 2019

8.11.4, April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

JavaScript

C++

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

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

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

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

yes

schema-free

yes

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

yes

SQL

Support of SQL

with Databricks SQL

yes

with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP REST

only for PouchDB Server
JavaScript API

C++ API
Java API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Python
R
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

View functions in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

with a proxy-based framework, named couchdb-lounge

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or 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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