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DBMS > Heroic vs. InfluxDB vs. MySQL vs. Titan

System Properties Comparison Heroic vs. InfluxDB vs. MySQL vs. Titan

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonInfluxDB  Xexclude from comparisonMySQL  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchDBMS for storing time series, events and metricsWidely used open source RDBMSTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS infoKey/Value like access via memcached APIGraph DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.57
Rank#250  Overall
#21  Time Series DBMS
Score26.56
Rank#28  Overall
#1  Time Series DBMS
Score1087.72
Rank#2  Overall
#2  Relational DBMS
Websitegithub.com/­spotify/­heroicwww.influxdata.com/­products/­influxdb-overviewwww.mysql.comgithub.com/­thinkaurelius/­titan
Technical documentationspotify.github.io/­heroicdocs.influxdata.com/­influxdbdev.mysql.com/­docgithub.com/­thinkaurelius/­titan/­wiki
DeveloperSpotifyOracle infosince 2010, originally MySQL AB, then SunAurelius, owned by DataStax
Initial release2014201319952012
Current release2.7.5, January 20248.3.0, January 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are availableOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageJavaGoC and C++Java
Server operating systemsLinux
OS X infothrough Homebrew
FreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Unix
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesNumeric 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.nonoyes
Secondary indexesyes infovia Elasticsearchnoyesyes
SQL infoSupport of SQLnoSQL-like query languageyes infowith proprietary extensionsno
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
HTTP API
JSON over UDP
ADO.NET
JDBC
ODBC
Proprietary native API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
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
Clojure
Java
Python
Server-side scripts infoStored proceduresnonoyes infoproprietary syntaxyes
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabricyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engineyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infonot for MyISAM storage engineACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engineyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoDepending on used storage engineyes
User concepts infoAccess controlsimple rights management via user accountsUsers with fine-grained authorization concept infono user groups or rolesUser authentification and security via Rexster Graph Server
More information provided by the system vendor
HeroicInfluxDBMySQLTitan
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 27,500 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
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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.

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More resources
HeroicInfluxDBMySQLTitan
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?
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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

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Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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