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Products

MANAGED BY US

Simplify and scale with Cloud services

InfluxDB Cloud Serverless
InfluxDB Cloud Dedicated

MANAGED BY YOU

For organizations that need full control

InfluxDB Clustered

INTEGRATIONS & COLLECTORS

300+ plugins, easy interoperability

Collectors
Client Libraries
Lakehouse / Warehouse

OTHER RESOURCES

Performance Comparisons
Find the Right Product
Platform Overview
Use Cases

Use Cases

DATA WORKLOADS

REAL-TIME ANALYTICS

Collect, analyze, and predict in real time

Infrastructure Monitoring
Real-Time Monitoring
DevOps Monitoring
Security Event Monitoring
Application Monitoring
Gaming Analytics

NETWORK & DEVICE TELEMETRY

Modernize telemetry data collection and analysis

Network Monitoring
Aerospace Monitoring
IoT Analytics

MODERN DATA HISTORIAN

Modernize operations with time series data

Renewable Energy Monitoring
Process Modernization
Digital Transformation
Predictive Maintenance

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Turn sensor data into actionable intelligence

Predictive Analytics
ML with Lakehouses

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Financial Services
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Manufacturing
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Developer Resources
Blog
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EVERY
SECOND
COUNTS.

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time series data.

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Query data immediately upon arrival for real-time insights across systems and
applications

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Monitor and control devices and sensors in IoT, network, and field deployments.

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MODERN DATA HISTORIAN

Unleash and transform on-site industrial OT data in the manufacturing plant and
on the factory floor.

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MACHINE LEARNING AND AI

Share real-time data with open ML/AI tools to create predictive analytics for
automated, intelligent applications and systems.

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REAL-TIME ANALYTICS

Query data immediately upon arrival for real-time insights across systems and
applications.

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NETWORK & DEVICE TELEMETRY

Monitor and control devices and sensors in IoT, network, and field deployments.

Learn More



MODERN DATA HISTORIAN

Unleash and transform on-site industrial OT data in the manufacturing plant and
on the factory floor.

Learn More



MACHINE LEARNING & AI

Share real-time data with open ML/AI tools to create predictive analytics for
intelligent applications and systems.

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PURPOSE-BUILT FOR REAL-TIME WITH PROVEN PERFORMANCE AT SCALE

SINGLE DATASTORE

Run analytics across multiple workload types with a single purpose-built
platform.

COLUMNAR DESIGN

Scales without limits with built-in storage and query performance optimization.

NATIVE SQL

Query directly with InfluxDB using standard SQL.

REAL-TIME QUERY

Sub-second query response on leading-edge data.

UNLIMITED CARDINALITY

Analyze billions of time series data points per second without limitations or
caps.

SUPERIOR DATA COMPRESSION

Maximize data compression to store more data at a fraction of the cost.


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Since the first availability of InfluxDB in 2012, InfluxData has stayed true to
its open source roots—first as a distributor, then as a user, and now as a
contributor.


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Today, InfluxDB deployments span multiple industries, with customers running at
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Monitor, optimize, and manage renewable energy and traditional power systems to
achieve smart grid balancing and optimization. Forecast and predict maintenance
needs for renewable energy sources, such as wind turbines and solar farms.

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Analyze network performance and usage patterns in telecommunication
infrastructure. Improve quality of service, optimize infrastructure resources,
and reduce operational costs.

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improve quality of life.

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and sensors.

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Get real-time insights from satellites, networks, and every stage of the launch
operation process. Reduce errors and accelerate time to market in this
mission-critical space.

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MANUFACTURING

Analyze production data streams in real-time to identify bottlenecks, prevent
downtime and power predictive maintenance for your industrial equipment.

Learn More



ENERGY AND UTILITIES

Monitor, optimize, and manage renewable energy and traditional power systems to
achieve smart grid balancing and optimization. Forecast and predict maintenance
needs for your renewable energy sources such as wind turbines and solar farms.

Learn More



TELECOMMUNICATIONS

Analyze network performance and usage patterns in telecommunication
infrastructure. Improve quality of service, optimize infrastructure resources,
and reduce operational costs.

Learn More



CONSUMER IOT

Use real-time monitoring and analytics to optimize energy consumption and
improve quality of life.

Learn More



INDUSTRIAL IOT

Optimize operational processes with real-time insights from industrial equipment
and sensors.

Learn More



AEROSPACE

Get real-time insights from satellites, networks, and every stage of the launch
operation process. Reduce errors and accelerate time to market in this
mission-critical space.

Learn More



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Source: DB Engines


CODE IN THE LANGUAGES YOU LOVE

No need to conform to a new language or technology. InfluxDB supports multiple
programming and query languages, with client libraries and integrations to make
things simple, all powered by a RESTful API.

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ReadWrite

                  from influxdb_client_3 import InfluxDBClient3
import pandas
import os

database = os.getenv('INFLUX_DATABASE')
token = os.getenv('INFLUX_TOKEN')
host="https://us-east-1-1.aws.cloud2.influxdata.com"

def querySQL():
  client = InfluxDBClient3(host, database=database, token=token)
  table = client.query(
    '''SELECT
        room,
        DATE_BIN(INTERVAL '1 day', time) AS _time,
        AVG(temp) AS temp,
        AVG(hum) AS hum,
        AVG(co) AS co
      FROM home
      WHERE time >= now() - INTERVAL '90 days'
      GROUP BY room, _time
      ORDER BY _time'''
  )

  print(table.to_pandas().to_markdown())

  client.close()
  
querySQL()
                  
Copy

c

                  from influxdb_client_3 import InfluxDBClient3
import os

database = os.getenv('INFLUX_DATABASE')
token = os.getenv('INFLUX_TOKEN')
host="https://us-east-1-1.aws.cloud2.influxdata.com"

def write_line_protocol():
  client = InfluxDBClient3(host, database=database, token=token)
  
  record = "home,room=Living\\ Room temp=22.2,hum=36.4,co=17i"
  
  print("Writing record:", record )
  client.write(record)
  
  client.close()

write_line_protocol()

                  
Copy

c

                  @main
struct QueryCpuData: AsyncParsableCommand {
  @Option(name: .shortAndLong, help: "The name or id of the bucket destination.")
  private var bucket: String

  @Option(name: .shortAndLong, help: "The name or id of the organization destination.")
  private var org: String

  @Option(name: .shortAndLong, help: "Authentication token.")
  private var token: String

  @Option(name: .shortAndLong, help: "HTTP address of InfluxDB.")
  private var url: String
}

extension QueryCpuData {
  mutating func run() async throws {
    //
    // Initialize Client with default Bucket and Organization
    //
    let client = InfluxDBClient(
            url: url,
            token: token,
            options: InfluxDBClient.InfluxDBOptions(bucket: bucket, org: org))

    // Flux query
    let query = """
                from(bucket: "\(self.bucket)")
                    |> range(start: -10m)
                    |> filter(fn: (r) => r["_measurement"] == "cpu")
                    |> filter(fn: (r) => r["cpu"] == "cpu-total")
                    |> filter(fn: (r) => r["_field"] == "usage_user" or r["_field"] == "usage_system")
                    |> last()
                """

    print("\nQuery to execute:\n\(query)\n")

    let response = try await client.queryAPI.queryRaw(query: query)

    let csv = String(decoding: response, as: UTF8.self)
    print("InfluxDB response: \(csv)")

    client.close()
  }
}
                  
Copy

c

                  import ArgumentParser
import Foundation
import InfluxDBSwift
import InfluxDBSwiftApis

@main
struct WriteData: AsyncParsableCommand {
  @Option(name: .shortAndLong, help: "The name or id of the bucket destination.")
  private var bucket: String

  @Option(name: .shortAndLong, help: "The name or id of the organization destination.")
  private var org: String

  @Option(name: .shortAndLong, help: "Authentication token.")
  private var token: String

  @Option(name: .shortAndLong, help: "HTTP address of InfluxDB.")
  private var url: String
}

extension WriteData {
  mutating func run() async throws {
    //
    // Initialize Client with default Bucket and Organization
    //
    let client = InfluxDBClient(
            url: url,
            token: token,
            options: InfluxDBClient.InfluxDBOptions(bucket: bucket, org: org))

    //
    // Record defined as Data Point
    //
    let recordPoint = InfluxDBClient
            .Point("demo")
            .addTag(key: "type", value: "point")
            .addField(key: "value", value: .int(2))
    //
    // Record defined as Data Point with Timestamp
    //
    let recordPointDate = InfluxDBClient
            .Point("demo")
            .addTag(key: "type", value: "point-timestamp")
            .addField(key: "value", value: .int(2))
            .time(time: .date(Date()))

    try await client.makeWriteAPI().write(points: [recordPoint, recordPointDate])
    print("Written data:\n\n\([recordPoint, recordPointDate].map { "\t- \($0)" }.joined(separator: "\n"))")
    print("\nSuccess!")

    client.close()
  }
}
                  
Copy

c

                  import {InfluxDBClient} from '@influxdata/influxdb3-client'
import {tableFromArrays} from 'apache-arrow';

const database = process.env.INFLUX_DATABASE;
const token = process.env.INFLUX_TOKEN;
const host = "https://us-east-1-1.aws.cloud2.influxdata.com";

async function main() {
    const client = new InfluxDBClient({host, token})
    const query = `
    SELECT
      room,
      DATE_BIN(INTERVAL '1 day', time) AS _time,
      AVG(temp) AS temp,
      AVG(hum) AS hum,
      AVG(co) AS co
    FROM home
    WHERE time >= now() - INTERVAL '90 days'
    GROUP BY room, _time
    ORDER BY _time
    `
    const result = await client.query(query, database)

    const data = {room: [], day: [], temp: []}

    for await (const row of result) {
      data.day.push(new Date(row._time).toISOString())
      data.room.push(row.room)
      data.temp.push(row.temp)
    }

    console.table([...tableFromArrays(data)])

    client.close()
}

main()
                  
Copy

c

                  import {InfluxDBClient} from '@influxdata/influxdb3-client'

const database = process.env.INFLUX_DATABASE;
const token = process.env.INFLUX_TOKEN;
const host = "https://us-east-1-1.aws.cloud2.influxdata.com";

async function main() {
    const client = new InfluxDBClient({host, token})

    const record = "home,room=Living\\ Room temp=22.2,hum=36.4,co=17i"
    await client.write(record, database)
    client.close()
}

main()
                  
Copy

c

                  package com.influxdb3.examples;

import com.influxdb.v3.client.InfluxDBClient;
import java.util.stream.Stream;

public final class Query {
    private Query() {
        //not called
    }

    /**
     * @throws Exception
     */
    public static void main() throws Exception {

        final String hostUrl = "https://us-east-1-1.aws.cloud2.influxdata.com";
        final char[] authToken = (System.getenv("INFLUX_TOKEN")).toCharArray();
        final String database = System.getenv("INFLUX_DATABASE");

        try (InfluxDBClient client = InfluxDBClient.getInstance(hostUrl, authToken, database)) {
            String sql = """
                SELECT
                    room,
                    DATE_BIN(INTERVAL '1 day', time) AS _time,
                    AVG(temp) AS temp, AVG(hum) AS hum, AVG(co) AS co
                FROM home
                WHERE time >= now() - INTERVAL '90 days'
                GROUP BY room, _time
                ORDER BY _time""";

            String layoutHeading = "| %-16s | %-12s | %-6s |%n";
            System.out.printf("--------------------------------------------------------%n");
            System.out.printf(layoutHeading, "day", "room", "temp");
            System.out.printf("--------------------------------------------------------%n");

            String layout = "| %-16s | %-12s | %.2f |%n";
            try (Stream stream = client.query(sql)) {
                stream.forEach(row -> System.out.printf(layout, row[1], row[0], row[2]));
            }
        }
    }
}
                  
Copy

c

                  package com.influxdb3.examples;

import com.influxdb.v3.client.InfluxDBClient;

public final class Write {

    public static void main() throws Exception {

        final String hostUrl = "https://us-east-1-1.aws.cloud2.influxdata.com";
        final char[] authToken = (System.getenv("INFLUX_TOKEN")).toCharArray();
        final String database = System.getenv("INFLUX_DATABASE");
        try (InfluxDBClient client = InfluxDBClient.getInstance(hostUrl, authToken, database)) {
            String record = "home,room=Living\\ Room temp=22.2,hum=36.4,co=17i";
            System.out.printf("Write record: %s%n", record);
            client.writeRecord(record);
        }
    }
}
                  
Copy

c

                  InfluxDB2::Client.use('https://localhost:8086', 'my-token', org: 'my-org') do |client|

  result = client
    .create_query_api
    .query_raw(query: 'from(bucket:"my-bucket") |> range(start: 1970-01-01) |> last()')
  puts result
end
                  
Copy

c

                  InfluxDB2::Client.use('https://localhost:8086', 'my-token',
                      bucket: 'my-bucket',
                      org: 'my-org',
                      precision: InfluxDB2::WritePrecision::NANOSECOND) do |client|

  write_api = client.create_write_api
  write_api.write(data: 'h2o,location=west value=33i 15')
end
                  
Copy

c

                  package example

import org.apache.pekko.actor.ActorSystem
import org.apache.pekko.stream.scaladsl.Sink
import com.influxdb.client.scala.InfluxDBClientScalaFactory
import com.influxdb.query.FluxRecord

import scala.concurrent.Await
import scala.concurrent.duration.Duration

object InfluxDB2ScalaExample {

  implicit val system: ActorSystem = ActorSystem("it-tests")

  def main(args: Array[String]): Unit = {

    val influxDBClient = InfluxDBClientScalaFactory
      .create("http://localhost:8086", "my-token".toCharArray, "my-org")

    val fluxQuery = ("from(bucket: \"my-bucket\")\n"
      + " |> range(start: -1d)"
      + " |> filter(fn: (r) => (r[\"_measurement\"] == \"cpu\" and r[\"_field\"] == \"usage_system\"))")

    //Result is returned as a stream
    val results = influxDBClient.getQueryScalaApi().query(fluxQuery)

    //Example of additional result stream processing on client side
    val sink = results
      //filter on client side using `filter` built-in operator
      .filter(it => "cpu0" == it.getValueByKey("cpu"))
      //take first 20 records
      .take(20)
      //print results
      .runWith(Sink.foreach[FluxRecord](it => println(s"Measurement: ${it.getMeasurement}, value: ${it.getValue}")
      ))

    // wait to finish
    Await.result(sink, Duration.Inf)

    influxDBClient.close()
    system.terminate()
  }
}
                  
Copy

c

                     
package com.influxdb.client.scala.internal

import org.apache.pekko.Done
import org.apache.pekko.stream.scaladsl.{Flow, Keep, Sink, Source}
import com.influxdb.client.InfluxDBClientOptions
import com.influxdb.client.domain.WritePrecision
import com.influxdb.client.internal.{AbstractWriteBlockingClient, AbstractWriteClient}
import com.influxdb.client.scala.WriteScalaApi
import com.influxdb.client.service.WriteService
import com.influxdb.client.write.{Point, WriteParameters}

import javax.annotation.Nonnull
import scala.collection.immutable.ListMap
import scala.concurrent.Future
import scala.jdk.CollectionConverters._

class WriteScalaApiImpl(@Nonnull service: WriteService, @Nonnull options: InfluxDBClientOptions)

  extends AbstractWriteBlockingClient(service, options) with WriteScalaApi {

  override def writeRecord(precision: Option[WritePrecision], bucket: Option[String], org: Option[String]): Sink[String, Future[Done]] = {
    Flow[String]
      .map(record => Seq(new AbstractWriteClient.BatchWriteDataRecord(record)))
      .toMat(Sink.foreach(batch => writeHttp(precision, bucket, org, batch)))(Keep.right)
  }

  override def writeRecords(precision: Option[WritePrecision], bucket: Option[String], org: Option[String]): Sink[Seq[String], Future[Done]] = {
    writeRecords(toWriteParameters(precision, bucket, org))
  }

  override def writeRecords(parameters: WriteParameters): Sink[Seq[String], Future[Done]] = {
    Flow[Seq[String]]
      .map(records => records.map(record => new AbstractWriteClient.BatchWriteDataRecord(record)))
      .toMat(Sink.foreach(batch => writeHttp(parameters, batch)))(Keep.right)
  }


  override def writePoint(bucket: Option[String], org: Option[String]): Sink[Point, Future[Done]] = {
    Flow[Point]
      .map(point => (point.getPrecision, Seq(new AbstractWriteClient.BatchWriteDataPoint(point, options))))
      .toMat(Sink.foreach(batch => writeHttp(Some(batch._1), bucket, org, batch._2)))(Keep.right)
  }

  override def writePoints(bucket: Option[String], org: Option[String]): Sink[Seq[Point], Future[Done]] = {
    writePoints(new WriteParameters(bucket.orNull, org.orNull, null, null))
  }

  override def writePoints(parameters: WriteParameters): Sink[Seq[Point], Future[Done]] = {
    Flow[Seq[Point]]
      // create ordered Map
      .map(records => records.foldRight(ListMap.empty[WritePrecision, Seq[Point]]) {
        case (point, map) => map.updated(point.getPrecision, point +: map.getOrElse(point.getPrecision, Seq()))
      }.toList.reverse)
      .map(grouped => grouped.map(group => (group._1, group._2.map(point => new AbstractWriteClient.BatchWriteDataPoint(point, options)))))
      .flatMapConcat(batches => Source(batches))
      .toMat(Sink.foreach(batch => writeHttp(parameters.copy(batch._1, options), batch._2)))(Keep.right)
  }

  override def writeMeasurement[M](precision: Option[WritePrecision], bucket: Option[String], org: Option[String]): Sink[M, Future[Done]] = {
    Flow[M]
      .map(measurement => {
        val parameters = toWriteParameters(precision, bucket, org)
        Seq(toMeasurementBatch(measurement, parameters.precisionSafe(options)))
      })
      .toMat(Sink.foreach(batch => writeHttp(precision, bucket, org, batch)))(Keep.right)
  }

  override def writeMeasurements[M](precision: Option[WritePrecision], bucket: Option[String], org: Option[String]): Sink[Seq[M], Future[Done]] = {
    writeMeasurements(toWriteParameters(precision, bucket, org))
  }

  override def writeMeasurements[M](parameters: WriteParameters): Sink[Seq[M], Future[Done]] = {
    Flow[Seq[M]]
      .map(records => records.map(record => toMeasurementBatch(record, parameters.precisionSafe(options))))
      .toMat(Sink.foreach(batch => writeHttp(parameters, batch)))(Keep.right)
  }

  private def writeHttp(precision: Option[WritePrecision], bucket: Option[String], org: Option[String], batch: Seq[AbstractWriteClient.BatchWriteData]): Done = {
    writeHttp(toWriteParameters(precision, bucket, org), batch)
  }

  private def writeHttp(parameters: WriteParameters, batch: Seq[AbstractWriteClient.BatchWriteData]): Done = {
    write(parameters, batch.toList.asJava.stream())
    Done.done()
  }

  private def toWriteParameters(precision: Option[WritePrecision], bucket: Option[String], org: Option[String]): WriteParameters = {
    val parameters = new WriteParameters(bucket.orNull, org.orNull, precision.orNull, null)
    parameters.check(options)
    parameters
  }
}

  


                  
Copy

c

                  package influxdbv3

import (
  "context"
  "fmt"
  "io"
  "os"
  "text/tabwriter"

  "github.com/apache/arrow/go/v12/arrow"
  "github.com/InfluxCommunity/influxdb3-go/influx"
)

func QuerySQL() error {
  url := "https://us-east-1-1.aws.cloud2.influxdata.com"
  token := os.Getenv("INFLUX_TOKEN")
  database := os.Getenv("INFLUX_DATABASE")
	
  client, err := influx.New(influx.Configs{
	HostURL: url,
	AuthToken: token,
  })

  defer func (client *influx.Client)  {
	err := client.Close()
	if err != nil {
		panic(err)
	}
  }(client)

  query := `
    SELECT
	  room,
	  DATE_BIN(INTERVAL '1 day', time) AS _time,
	  AVG(temp) AS temp,
	  AVG(hum) AS hum,
	  AVG(co) AS co
	FROM home
	WHERE time >= now() - INTERVAL '90 days'
	GROUP BY room, _time
	ORDER BY _time
`

  iterator, err := client.Query(context.Background(), database, query)

  if err != nil {
    panic(err)
  }

  w := tabwriter.NewWriter(io.Discard, 4, 4, 1, ' ', 0)
  w.Init(os.Stdout, 0, 8, 0, '\t', 0)
  fmt.Fprintln(w, "day\troom\ttemp")

  for iterator.Next() {
	row := iterator.Value()
	day := (row["_time"].(arrow.Timestamp)).ToTime(arrow.TimeUnit(arrow.Nanosecond))
	fmt.Fprintf(w, "%s\t%s\t%.2f\n", day, row["room"], row["temp"])
  }

  w.Flush()
  return nil
}
                  
Copy

c

                  package influxdbv3

import (
  "context"
  "os"
  "fmt"
  "github.com/InfluxCommunity/influxdb3-go/influx"
)

func WriteLineProtocol() error {
  url := "https://us-east-1-1.aws.cloud2.influxdata.com"
  token := os.Getenv("INFLUX_TOKEN")
  database := os.Getenv("INFLUX_DATABASE")
	
  client, err := influx.New(influx.Configs{
	HostURL: url,
	AuthToken: token,
  })

  defer func (client *influx.Client)  {
	err := client.Close()
	if err != nil {
		panic(err)
	}
  }(client)

  record := "home,room=Living\\ Room temp=22.2,hum=36.4,co=17i"
  fmt.Println("Writing record: ", record)
  err = client.Write(context.Background(), database, []byte(record))

  if err != nil {
    panic(err)
  }
  return nil
}
                  
Copy

c

                  using System;
using System.Threading.Tasks;
using InfluxDB3.Client;
using InfluxDB3.Client.Query;

namespace InfluxDBv3;

public class Query
{
  static async Task QuerySQL()
  {
    const string hostUrl = "https://us-east-1-1.aws.cloud2.influxdata.com";
    string? database = System.Environment.GetEnvironmentVariable("INFLUX_DATABASE");
    string? authToken = System.Environment.GetEnvironmentVariable("INFLUX_TOKEN");

    using var client = new InfluxDBClient(hostUrl, authToken: authToken, database: database);
  
    const string sql = @"
      SELECT
        room,
        DATE_BIN(INTERVAL '1 day', time) AS _time,
        AVG(temp) AS temp,
        AVG(hum) AS hum,
        AVG(co) AS co
      FROM home
      WHERE time >= now() - INTERVAL '90 days'
      GROUP BY room, _time
      ORDER BY _time
    ";

    Console.WriteLine("{0,-30}{1,-15}{2,-15}", "day", "room", "temp");
    await foreach (var row in client.Query(query: sql))
    {
      Console.WriteLine("{0,-30}{1,-15}{2,-15}", row[1], row[0], row[2]);
    }

    Console.WriteLine();
  }
}
                  
Copy

c

                  using System;
using System.Threading.Tasks;
using InfluxDB3.Client;
using InfluxDB3.Client.Query;

namespace InfluxDBv3;

public class Write
{
  public static async Task WriteLineProtocol()
  {
    const string hostUrl = "https://us-east-1-1.aws.cloud2.influxdata.com";
    string? database = System.Environment.GetEnvironmentVariable("INFLUX_DATABASE");
    string? authToken = System.Environment.GetEnvironmentVariable("INFLUX_TOKEN");

    using var client = new InfluxDBClient(hostUrl, authToken: authToken, database: database);

    const string record = "home,room=Living\\ Room temp=22.2,hum=36.4,co=17i";
    Console.WriteLine("Write record: {0,-30}", record);
    await client.WriteRecordAsync(record: record);
  }
}

                  
Copy

c

                  client <- InfluxDBClient$new(url = "http://localhost:8086",
                             token = "my-token",
                             org = "my-org")
                            
data <- client$query('from(bucket: "my-bucket") |> range(start: -1h) |> drop(columns: ["_start", "_stop"])')
data
                  
Copy

c

                  client <- InfluxDBClient$new(url = "http://localhost:8086",
                             token = "my-token",
                             org = "my-org")
data <- ...
response <- client$write(data, bucket = "my-bucket", precision = "us",
                         measurementCol = "name",
                         tagCols = c("region", "sensor_id"),
                         fieldCols = c("altitude", "temperature"),
                         timeCol = "time")
                  
Copy

c
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