DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Doris vs. atoti vs. InfluxDB vs. Vitess

System Properties Comparison Apache Doris vs. atoti vs. InfluxDB vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Doris  Xexclude from comparisonatoti  Xexclude from comparisonInfluxDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAn MPP-based analytics DBMS embracing the MySQL protocolAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.DBMS for storing time series, events and metricsScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSObject oriented 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
Score0.60
Rank#247  Overall
#113  Relational DBMS
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitedoris.apache.org
github.com/­apache/­doris
atoti.iowww.influxdata.com/­products/­influxdb-overviewvitess.io
Technical documentationgithub.com/­apache/­doris/­wikidocs.atoti.iodocs.influxdata.com/­influxdbvitess.io/­docs
DeveloperApache Software Foundation, originally contributed from BaiduActiveViamThe Linux Foundation, PlanetScale
Initial release201720132013
Current release1.2.2, February 20232.7.6, April 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree versions availableOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoApache Version 2.0, commercial licenses available
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.
Implementation languageJavaJavaGoGo
Server operating systemsLinuxLinux
OS X infothrough Homebrew
Docker
Linux
macOS
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumeric data and Stringsyes
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 indexesyesnoyes
SQL infoSupport of SQLyesMultidimensional Expressions (MDX)SQL-like query languageyes infowith proprietary extensions
APIs and other access methodsJDBC
MySQL client
HTTP API
JSON over UDP
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJava.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
Server-side scripts infoStored proceduresuser defined functionsPythonnoyes infoproprietary syntax
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding, horizontal partitioningSharding infoin enterprise version onlySharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual 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 datanoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infotable locks or row locks depending on storage engine
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.noyesyes infoDepending on used storage engineyes
User concepts infoAccess controlfine grained access rights according to SQL-standardsimple rights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Apache DorisatotiInfluxDBVitess
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

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 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
Apache DorisatotiInfluxDBVitess
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

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

Workload Isolation in Apache Doris: Optimizing Resource Management and Performance
25 May 2024, hackernoon.com

How to Digest 15 Billion Logs Per Day and Keep Big Queries Within 1 Second
1 September 2023, KDnuggets

Streamlining Data Operations: How a Grocery Chain Optimizes Workloads with Apache Doris
16 May 2024, hackernoon.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

provided by Google News

Best use of cloud: ActiveViam
28 November 2023, Risk.net

FRTB product of the year: ActiveViam
28 November 2023, Risk.net

provided by Google News

Amazon Timestream for InfluxDB is now generally available
15 March 2024, AWS Blog

Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB?
5 June 2024, hackernoon.com

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

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

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

PlanetScale Serves up Vitess-Powered Serverless MySQL
23 November 2021, The New Stack

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

provided by Google News



Share this page

Featured Products

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

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

Present your product here