DB-EnginesextremeDB - solve IoT connectivity disruptionsEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by Redgate Software

DBMS > Apache Spark (SQL) vs. InfluxDB

System Properties Comparison Apache Spark (SQL) vs. InfluxDB

Please select another system to include it in the comparison.

Our visitors often compare Apache Spark (SQL) and InfluxDB with PostgreSQL, TimescaleDB and MySQL.

Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonInfluxDB  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingDBMS for storing time series, events and metrics
Primary database modelRelational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.76
Rank#30  Overall
#18  Relational DBMS
Score21.50
Rank#28  Overall
#1  Time Series DBMS
Websitespark.apache.org/­sqlwww.influxdata.com/­products/­influxdb-overview
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.influxdata.com/­influxdb
DeveloperApache Software Foundation
Initial release20142013
Current release3.5.0 ( 2.13), September 20232.7.6, April 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoMIT-License; commercial enterprise version available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaGo
Server operating systemsLinux
OS X
Windows
Linux
OS X infothrough Homebrew
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesNumeric data and Strings
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.nono
Secondary indexesnono
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsJDBC
ODBC
HTTP API
JSON over UDP
Supported programming languagesJava
Python
R
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoin enterprise version only
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infoin enterprise version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsno
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoDepending on used storage engine
User concepts infoAccess controlnosimple rights management via user accounts
More information provided by the system vendor
Apache Spark (SQL)InfluxDB
News

Telegraf 1.34 Release Notes
12 March 2025

Alerting with InfluxDB 3 Core and Enterprise
11 March 2025

An Introduction to Database Security
6 March 2025

Building Your First Python Plugin for the InfluxDB 3 Processing Engine
4 March 2025

InfluxDB 3 Core and Enterprise Architecture Highlights
27 February 2025

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

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

More resources
Apache Spark (SQL)InfluxDB
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

show all



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

SingleStore logo

The data platform to build your intelligent applications.
Try it free.

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here