DBMS > Databricks vs. Hazelcast vs. Microsoft Access vs. MySQL vs. SWC-DB

System Properties Comparison Databricks vs. Hazelcast vs. Microsoft Access vs. MySQL vs. SWC-DB

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.

A widely adopted in-memory data grid

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 high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

Wide column store

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

Time Series DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	84.24
Rank	#14	Overall
	#2	Document stores
	#9	Relational DBMS

Score	5.72
Rank	#59	Overall
	#6	Key-value stores

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Score	1029.49
Rank	#2	Overall
	#2	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Website

www.databricks.com

hazelcast.com

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

www.mysql.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.databricks.com

hazelcast.org/imdg/docs

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Databricks

Hazelcast

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Alex Kashirin

Initial release

2013

2008

1992

1995

2020

Current release

5.3.6, November 2023

1902 (16.0.11328.20222), March 2019

9.0.0, July 2024

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL V3

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

Java

C++

C and C++

C++

Server operating systems

hosted

All OS with a Java VM

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

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

schema-free

yes

schema-free

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

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

SQL-like query language

yes

but not compliant to any SQL standard

yes

with proprietary extensions

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol
Thrift

Supported programming languages

Python
R
Scala

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
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++

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Event Listeners, Executor Services

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

Events

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

none

Multi-source replication
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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

one or two-phase-commit; repeatable reads; read commited

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

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

User concepts

Access control

Role-based 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

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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