DBMS > InfluxDB vs. MySQL vs. Neo4j vs. PostgreSQL vs. Vitess
System Properties Comparison InfluxDB vs. MySQL vs. Neo4j vs. PostgreSQL vs. Vitess
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| Name | InfluxDB Xexclude from comparison | MySQL Xexclude from comparison | Neo4j Xexclude from comparison | PostgreSQL Xexclude from comparison | Vitess Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Description | DBMS for storing time series, events and metrics | Widely used open source RDBMS | Scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings | Widely used open source RDBMS  Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL | Scalable, distributed, cloud-native DBMS, extending MySQL | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Primary database model | Time Series DBMS | Relational DBMS Key/Value like access via memcached API | Graph DBMS | Relational DBMS with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module. | Relational DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary database models | Spatial DBMS with GEO package | Document store Spatial DBMS | Document store Graph DBMS with Apache AgeSpatial DBMS Vector DBMS with pgvector extension | Document store Spatial DBMS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Website | www.influxdata.com/products/influxdb-overview | www.mysql.com | neo4j.com | www.postgresql.org | vitess.io | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Technical documentation | docs.influxdata.com/influxdb | dev.mysql.com/doc | neo4j.com/docs | www.postgresql.org/docs | vitess.io/docs | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Developer | Oracle since 2010, originally MySQL AB, then Sun | Neo4j, Inc. | PostgreSQL Global Development Group www.postgresql.org/developer | The Linux Foundation, PlanetScale | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Initial release | 2013 | 1995 | 2007 | 1989 1989: Postgres, 1996: PostgreSQL | 2013 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Current release | 2.7.6, April 2024 | 8.4.0, April 2024 | 5.20, May 2024 | 16.3, May 2024 | 15.0.2, December 2022 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| License Commercial or Open Source | Open Source MIT-License; commercial enterprise version available | Open Source GPL version 2. Commercial licenses with extended functionallity are available | Open Source GPL version3, commercial licenses available | Open Source BSD | Open Source Apache Version 2.0, commercial licenses available | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Cloud-based only Only available as a cloud service | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DBaaS offerings (sponsored links) Database 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. | Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers. |
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| Implementation language | Go | C and C++ | Java, Scala | C | Go | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Server operating systems | Linux OS X through Homebrew | FreeBSD Linux OS X Solaris Windows | Linux Can also be used server-less as embedded Java database. OS X Solaris Windows | FreeBSD HP-UX Linux NetBSD OpenBSD OS X Solaris Unix Windows | Docker Linux macOS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Data scheme | schema-free | yes | schema-free and schema-optional | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typing predefined data types such as float or date | Numeric data and Strings | yes | yes | yes | 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. | no | yes | yes specific XML-type available, but no XML query functionality. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Secondary indexes | no | yes | yes pluggable indexing subsystem, by default Apache Lucene | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| SQL Support of SQL | SQL-like query language | yes with proprietary extensions | no | yes standard with numerous extensions | yes with proprietary extensions | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| APIs and other access methods | HTTP API JSON over UDP | ADO.NET JDBC ODBC Proprietary native API | Bolt protocol Cypher query language Java API Neo4j-OGM Object Graph MapperRESTful HTTP API Spring Data Neo4j TinkerPop 3 | ADO.NET JDBC native C library ODBC streaming API for large objects | ADO.NET JDBC MySQL protocol 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 | .Net Clojure Elixir Go Groovy Haskell Java JavaScript Perl PHP Python Ruby Scala | .Net C C++ Delphi Java JDBCJavaScript (Node.js) Perl PHP Python Tcl | 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 | no | yes proprietary syntax | yes User defined Procedures and Functions | user defined functions realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc. | yes proprietary syntax | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Triggers | no | yes | yes via event handler | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Partitioning methods Methods for storing different data on different nodes | Sharding in enterprise version only | horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric | yes using Neo4j Fabric | partitioning by range, list and (since PostgreSQL 11) by hash | Sharding | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor in enterprise version only | Multi-source replication Source-replica replication | Causal Clustering using Raft protocol available in in Enterprise Version only | Source-replica replication other methods possible by using 3rd party extensions | Multi-source replication Source-replica replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| MapReduce Offers an API for user-defined Map/Reduce methods | no | no | no | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Causal and Eventual Consistency configurable in Causal Cluster setup Immediate Consistency in stand-alone mode | Immediate Consistency | Eventual Consistency across shards Immediate Consistency within a shard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Foreign keys Referential integrity | no | yes not for MyISAM storage engine | yes Relationships in graphs | yes | yes not for MyISAM storage engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no | ACID not for MyISAM storage engine | ACID | ACID | ACID at shard level | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Concurrency Support for concurrent manipulation of data | yes | yes table locks or row locks depending on storage engine | yes | yes | yes table locks or row locks depending on storage engine | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | yes Depending on used storage engine | yes | no | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| User concepts Access control | simple rights management via user accounts | Users with fine-grained authorization concept no user groups or roles | Users, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos) | fine grained access rights according to SQL-standard | Users with fine-grained authorization concept no user groups or roles | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| InfluxDB | MySQL | Neo4j | PostgreSQL | Vitess | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Specific characteristics | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Neo4j delivers graph technology that has been battle tested for performance and scale... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Competitive advantages | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Neo4j is the market leader, graph database category creator, and the most widely... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Typical application scenarios | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Real-Time Recommendations Master Data Management Identity and Access Management Network... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Key customers | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Over 800 commercial customers and over 4300 startups use Neo4j. Flagship customers... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Market metrics | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | Neo4j boasts the world's largest graph database ecosystem with more than 140 million... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Licensing and pricing models | Open source core with closed source clustering available either on-premise or on... » more | GPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial... » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| News | Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB Deadman Alerts with Grafana and InfluxDB Cloud 3.0 Chasing the Skies: Monitoring Flights with InfluxDB Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS | This Week in Neo4j: Podcast, Testing, Knowledge Graph, GenAI and more Neo4j and Snowflake Bring Graph Data Science Into the AI Data Cloud RDF vs. Property Graphs: Choosing the Right Approach for Implementing a Knowledge Graph This Week in Neo4j: Importing Data, NODES, GenAI, Going Meta and more openCypher Will Pave the Road to GQL for Cypher Implementers | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| InfluxDB | MySQL | Neo4j | PostgreSQL | Vitess | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| DB-Engines blog posts | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | MySQL is the DBMS of the Year 2019 MariaDB strengthens its position in the open source RDBMS market The struggle for the hegemony in Oracle's database empire | Applying Graph Analytics to Game of Thrones MySQL, PostgreSQL and Redis are the winners of the March ranking The openCypher Project: Help Shape the SQL for Graphs | PostgreSQL is the DBMS of the Year 2023 Snowflake is the DBMS of the Year 2022, defending the title from last year Snowflake is the DBMS of the Year 2021 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Recent citations in the news | Amazon Timestream for InfluxDB is now generally available Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB? Amazon Timestream: Managed InfluxDB for Time Series Data InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency provided by Google News | Amazon Aurora MySQL version 2 (with MySQL 5.7 compatibility) to version 3 (with MySQL 8.0 compatibility) upgrade ... Enterprise Manager: How Comcast enhanced monitoring for MySQL InnoDB Clusters Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs Ultimate MySQL Workbench Installation Guide [2024 Edition] How to Create a MySQL 8 Database User With Remote Access provided by Google News | Neo4j graph analytics integrated with Snowflake's AI cloud – Blocks and Files Neo4j integrates dozens of graph analytics functions with data in Snowflake Neo4j & Snowflake Collaborate for AI Insights & Analytics Neo4j Announces Collaboration with Microsoft to Advance GenAI and Data Solutions USA - English - India - English Neo4j Partners with Snowflake for Advanced AI Insights and Predictive Analytics provided by Google News | PostgreSQL Tutorial: Definition, Commands, & Features Raise the bar on AI-powered app development with Azure Database for PostgreSQL How To Schedule PostgreSQL Backups With GitHub Actions How to implement a better like, views, comment counters in PostgreSQL? Enterprise DB begins rolling AI features into PostgreSQL provided by Google News | PlanetScale Unveils Distributed MySQL Database Service Based on Vitess PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes They scaled YouTube -- now they’ll shard everyone with PlanetScale PlanetScale Serves up Vitess-Powered Serverless MySQL Massively Scaling MySQL Using Vitess provided by Google News | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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