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DBMS > InfluxDB vs. MySQL vs. Spark SQL

System Properties Comparison InfluxDB vs. MySQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonMySQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsWidely used open source RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelTime Series DBMSRelational DBMS infoKey/Value like access via memcached APIRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score28.48
Rank#28  Overall
#1  Time Series DBMS
Score1106.67
Rank#2  Overall
#2  Relational DBMS
Score19.78
Rank#36  Overall
#22  Relational DBMS
Websitewww.influxdata.com/­products/­influxdb-overviewwww.mysql.comspark.apache.org/­sql
Technical documentationdocs.influxdata.com/­influxdbdev.mysql.com/­docspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperOracle infosince 2010, originally MySQL AB, then SunApache Software Foundation
Initial release201319952014
Current release2.7.5, January 20248.3.0, January 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
  • PlanetScale: Deploy a fully managed database with the reliability of MySQL and the scale of open source Vitess with PlanetScale today. Predictably scale, increase workflow velocity, and deploy features with zero downtime.
  • Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageGoC and C++Scala
Server operating systemsLinux
OS X infothrough Homebrew
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateNumeric data and Stringsyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesnoyesno
SQL infoSupport of SQLSQL-like query languageyes infowith proprietary extensionsSQL-like DML and DDL statements
APIs and other access methodsHTTP API
JSON over UDP
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
Supported programming languages.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoproprietary syntaxno
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyes infonot for MyISAM storage engineno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infonot for MyISAM storage engineno
Concurrency infoSupport for concurrent manipulation of datayesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engineyesno
User concepts infoAccess controlsimple rights management via user accountsUsers with fine-grained authorization concept infono user groups or rolesno
More information provided by the system vendor
InfluxDBMySQLSpark SQL
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 25,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
News

Time Series Data and OLAP: Why You Should Use InfluxDB for Real-Time Analytics
23 February 2024

InfluxDB 3.0: The Ideal Solution for Real-Time Analytics
21 February 2024

How Time Series Databases and Data Lakes Work Together
19 February 2024

Using Time Series Data for Infrastructure Monitoring: Challenges and Advantages
16 February 2024

Powering Real-Time Data Processing with InfluxDB and AWS Kinesis
14 February 2024

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.

Related products and services
3rd partiesNavicat Monitor is a safe, simple and agentless remote server monitoring tool for MySQL and many other database management systems.
» more

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
» more

Navicat for MySQL is the ideal solution for MySQL/MariaDB administration and development.
» more

PlanetScale: Deploy a fully managed serverless database with the reliability of MySQL and the tested scalability of Vitess. Predictably scale, increase workflow velocity, and deploy features with zero downtime.
Get started with a PlanetScale database today for free.
» more

CData: Connect to Big Data & NoSQL through standard Drivers.
» more

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
InfluxDBMySQLSpark SQL
DB-Engines blog posts

Why Build a Time Series Data Platform?
20 July 2017, Paul Dix (guest author)

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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MySQL is the DBMS of the Year 2019
3 January 2020, Matthias Gelbmann, Paul Andlinger

MariaDB strengthens its position in the open source RDBMS market
5 April 2018, Matthias Gelbmann

The struggle for the hegemony in Oracle's database empire
2 May 2017, Paul Andlinger

show all

Recent citations in the news

Install the InfluxDB Time-Series Database on Ubuntu Server 22.04
21 October 2023, The New Stack

How Apache Arrow accelerates InfluxDB
21 November 2023, InfoWorld

Inside InfluxDB 3.0: Exploring InfluxDB's Scalable and Decoupled Architecture
15 August 2023, InfoQ.com

InfluxData apologizes for deleting cloud regions without performing 'scream test'
11 July 2023, The Register

InfluxData Announces InfluxDB Clustered to Deliver Time Series Analytics for On-Premises and Private Cloud ...
6 September 2023, Business Wire

provided by Google News

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19 February 2024, InfoQ.com

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Oracle introduces JavaScript support in MySQL
3 January 2024, InfoWorld

Oracle Introduces MySQL HeatWave Lakehouse, Outperforming Databricks, Snowflake & BigQuery
21 July 2023, Forbes

provided by Google News

Run Spark SQL on Amazon Athena Spark
23 October 2023, AWS Blog

1.5 Years of Spark Knowledge in 8 Tips | by Michael Berk | Dec, 2023
23 December 2023, Towards Data Science

The Evolution of Contexts in Apache Spark | by Ethiraj Srinivasan | Technology Hits | Jan, 2024
4 January 2024, Medium

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2023
12 July 2023, Simplilearn

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

provided by Google News



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