DBMS > Databricks vs. Interbase vs. MySQL vs. SQLite vs. Trafodion

System Properties Comparison Databricks vs. Interbase vs. MySQL vs. SQLite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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.

Light-weight proven RDBMS

originally from Borland

Widely used open source RDBMS

Widely used embeddable, in-process RDBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

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	4.61
Rank	#72	Overall
	#39	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

www.databricks.com

www.embarcadero.com/products/interbase

www.mysql.com

www.sqlite.org

trafodion.apache.org

Technical documentation

docs.databricks.com

docs.embarcadero.com/products/interbase

dev.mysql.com/doc

www.sqlite.org/docs.html

trafodion.apache.org/documentation.html

Developer

Databricks

Embarcadero

Oracle

since 2010, originally MySQL AB, then Sun

Dwayne Richard Hipp

Apache Software Foundation, originally developed by HP

Initial release

2013

1984

1995

2000

2014

Current release

InterBase 2020, December 2019

8.4.0, April 2024

3.45.3 (15 April 2024), April 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Public Domain

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

C++, Java

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

server-less

Linux

Data scheme

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

yes

dynamic column types

yes

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

export as XML data possible

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

with proprietary extensions

yes

SQL-92 is not fully supported

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
ODBC

Supported programming languages

Python
R
Scala

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Interbase procedure and trigger language

yes

proprietary syntax

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

Multi-source replication
Source-replica replication

none

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

table locks or row locks depending on storage engine

yes

via file-system locks

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

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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