DBMS > Apache Spark (SQL) vs. FileMaker vs. MySQL

System Properties Comparison Apache Spark (SQL) vs. FileMaker vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

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

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Widely used open source RDBMS

Primary database model

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	20.40
Rank	#29	Overall
	#18	Relational DBMS

Score	36.48
Rank	#21	Overall
	#14	Relational DBMS

Score	987.11
Rank	#2	Overall
	#2	Relational DBMS

Website

spark.apache.org/sql

www.claris.com/filemaker

www.mysql.com

Technical documentation

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

www.claris.com/resources/documentation

dev.mysql.com/doc

Developer

Apache Software Foundation

Claris

a subsidiary of Apple

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2014

1983

1995

Current release

3.5.0 ( 2.13), September 2023

19.4.1, November 2021

9.0.0, July 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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

Scala

C and C++

Server operating systems

Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

via plugins

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Filemaker WebDirect
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python
R
Scala

PHP

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

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes, utilizing Spark Core

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication, warm standby

since Version 14

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

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

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

In-memory capabilities

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

yes

User concepts

Access control

simple rights management via user accounts and connection to external directory services

Users with fine-grained authorization concept

no user groups or roles

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