DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > InfluxDB vs. Machbase Neo vs. Vitess

System Properties Comparison InfluxDB vs. Machbase Neo vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameInfluxDB  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionDBMS for storing time series, events and metricsTimeSeries DBMS for AIoT and BigDataScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score25.83
Rank#28  Overall
#1  Time Series DBMS
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitewww.influxdata.com/­products/­influxdb-overviewmachbase.comvitess.io
Technical documentationdocs.influxdata.com/­influxdbmachbase.com/­dbmsvitess.io/­docs
DeveloperMachbaseThe Linux Foundation, PlanetScale
Initial release201320132013
Current release2.7.6, April 2024V8.0, August 202315.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoMIT-License; commercial enterprise version availablecommercial infofree test version availableOpen Source infoApache Version 2.0, commercial licenses available
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.
Implementation languageGoCGo
Server operating systemsLinux
OS X infothrough Homebrew
Linux
macOS
Windows
Docker
Linux
macOS
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageyes infowith proprietary extensions
APIs and other access methodsHTTP API
JSON over UDP
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
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
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
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 infoStored proceduresnonoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoin enterprise version onlyShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infoin enterprise version onlyselectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoDepending on used storage engineyes infovolatile and lookup tableyes
User concepts infoAccess controlsimple rights management via user accountssimple password-based access controlUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
InfluxDBMachbase Neo infoFormer name was InfinifluxVitess
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
News

What is DevRel at InfluxData
21 May 2024

An Introductory Guide to Grafana Alerts
16 May 2024

What to Expect When You’re Expecting InfluxDB: A Guide
14 May 2024

Introduction to Apache Iceberg
9 May 2024

Converting Timestamp to Date in Java
7 May 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

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

More resources
InfluxDBMachbase Neo infoFormer name was InfinifluxVitess
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

Recent citations in the news

Introducing Amazon Timestream for InfluxDB: A managed service for the popular open source time-series database ...
20 May 2024, AWS Blog

Amazon Timestream: Managed InfluxDB for Time Series Data
14 March 2024, The New Stack

InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World
14 March 2024, Business Wire

How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency
15 March 2024, Datanami

Run and manage open source InfluxDB databases with Amazon Timestream | Amazon Web Services
14 March 2024, AWS Blog

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



Share this page

Featured Products

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

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

Milvus logo

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

Neo4j logo

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

RaimaDB logo

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

Present your product here