DBMS > Databricks vs. Drizzle vs. Ehcache vs. MySQL

System Properties Comparison Databricks vs. Drizzle vs. Ehcache vs. MySQL

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle 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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A widely adopted Java cache with tiered storage options

Widely used open source RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
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	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

www.databricks.com

www.ehcache.org

www.mysql.com

Technical documentation

docs.databricks.com

www.ehcache.org/documentation

dev.mysql.com/doc

Developer

Databricks

Drizzle project, originally started by Brian Aker

Terracotta Inc, owned by Software AG

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2013

2008

2009

1995

Current release

7.2.4, September 2012

3.10.0, March 2022

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache Version 2; commercial licenses available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X

All OS with a Java VM

FreeBSD
Linux
OS X
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

SQL

Support of SQL

with Databricks SQL

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC

JCache

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Python
R
Scala

C
C++
Java
PHP

Java

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

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

proprietary syntax

Triggers

hooks for callbacks inside the server can be used.

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

yes

by using Terracotta Server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

yes

supports JTA and can work as an XA resource

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Users with fine-grained authorization concept

no user groups or roles

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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