DBMS > Databricks vs. Microsoft Access vs. MySQL vs. Oracle NoSQL vs. WakandaDB

System Properties Comparison Databricks vs. Microsoft Access vs. MySQL vs. Oracle NoSQL vs. WakandaDB

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.

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used open source RDBMS

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Document store
Key-value store
Relational DBMS

Object oriented DBMS

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	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

www.databricks.com

www.microsoft.com/en-us/microsoft-365/access

www.mysql.com

www.oracle.com/database/nosql/technologies/nosql

wakanda.github.io

Technical documentation

docs.databricks.com

developer.microsoft.com/en-us/access

dev.mysql.com/doc

docs.oracle.com/en/database/other-databases/nosql-database/index.html

wakanda.github.io/doc

Developer

Databricks

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Oracle

Wakanda SAS

Initial release

2013

1992

1995

2011

2012

Current release

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

24.1, May 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and C++

Java

C++, JavaScript

Server operating systems

hosted

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Windows

Data scheme

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

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like DML and DDL statements

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

Python
R
Scala

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

C
C#
Go
Java
JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

yes

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

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

but no files for transaction logging

ACID

not for MyISAM storage engine

configurable

ACID within a storage node (=shard)

ACID

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

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

off heap cache

User concepts

Access control

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

yes

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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