DBMS > Apache Druid vs. MariaDB vs. Microsoft Access vs. Spark SQL

System Properties Comparison Apache Druid vs. MariaDB vs. Microsoft Access vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

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.)

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

druid.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

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

spark.apache.org/sql

Technical documentation

druid.apache.org/docs/latest/design

mariadb.com/kb/en/library

developer.microsoft.com/en-us/access

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Apache Software Foundation and contributors

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Microsoft

Apache Software Foundation

Initial release

2012

2009

Fork of MySQL, which was first released in 1995

1992

2014

Current release

29.0.1, April 2024

11.3.2, February 2024

1902 (16.0.11328.20222), March 2019

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPL version 2, commercial enterprise subscription available

commercial

Bundled with Microsoft Office

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

C++

Scala

Server operating systems

Linux
OS X
Unix

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Windows

Not a real database server, but making use of DLLs

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

Dynamic columns are supported

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

SQL for querying

yes

with proprietary extensions

yes

but not compliant to any SQL standard

SQL-like DML and DDL statements

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
DAO
ODBC
OLE DB

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

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

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

PL/SQL compatibility added with version 10.3

yes

since Access 2010 using the ACE-engine

Triggers

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

several options for horizontal partitioning and Sharding

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

not for in-memory storage engine

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

with MEMORY storage engine

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

Specific characteristics

MariaDB is the most powerful open source relational database – modern SQL and JSON...
» more

Competitive advantages

MariaDB Servers have many features unavailable in other open source relational databases....
» more

Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
» more

Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
» more

Market metrics

MariaDB is the default database in the LAMP stack supplied by Red Hat and SUSE Linux,...
» more

Licensing and pricing models

MariaDB plc subscriptions cover our free, open source database, Community Server,...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.