Time series starts with InfluxDB

The database for real-time systems powering physical AI

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Built for systems that can’t afford to lag. Capture, analyze, and act on high-resolution operational data in real-time.

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Time series database
Source: DB Engines

Most databases weren’t built for time series

Telemetry, edge devices, and physical AI generate data that most databases can’t handle. InfluxDB handles continuous, high-resolution data with precision and speed.

Engineered for performance at scale

Handle continuous, high-resolution data without breaking cost, latency, or reliability

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Real-time performance without cost runaway

Ingest at millions of data points per second while keeping storage and compute predictable

Edge-to-cloud continuity

Capture data where it’s generated and analyze it anywhere without redesigning your pipeline

Purpose-built architecture for continuous data

Optimized for fast ingest on high-velocity, high-resolution data with efficient compression and storage

Integrates with your stack

Deploy fast, scale seamlessly, and easily integrate without requiring specialized infrastructure

High-Speed Ingest

Ingest millions of series without impacting performance.

Real-Time Analytics

Transform and analyze unlimited series in real-time.

Eviction and Lakehouse Integration

Automatically evicts cold data and streams it into lakes, warehouses, and AI/ML pipelines.

Compression and Downsampling

Best-in-class compression. Parquet files store more data with less space.

Purpose-built for the world's most demanding systems

From grid stability to satellite telemetry, InfluxDB powers the systems that can't afford to lag.

Aerospace

Aerospace telemetry never stops. Stay ahead with a database built for speed, precision, and decades of data.

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Energy & Utilities

Power modern energy systems with real-time insights that maximize efficiency and reduce downtime.

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Modern Data Historian

Upgrade your historian for Industry 4.0 with real-time data that drives efficiency and lowers costs.

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Physical AI runs on time series

Close the loop between telemetry and action.

AI systems need a stream of high-precision telemetry to improve. InfluxDB captures granular sensor data enabling AI to detect, respond and predict in real-time.

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Aerospace

Aircraft and spacecraft require pinpoint precision for mission critical navigation. Capture high-rate sensor streams to power real-time diagnostics and adaptive control.

Manufacturing

Production lines generate constant signals. Feed real-time telemetry into AI models to predict equipment failures, optimize throughput, and maintain product quality.

Energy & Utilities

Manage grid volatility across distributed assets. Real-time sensor streams feed predictive models to prevent costly edge failures.

Build systems and infrastructure monitoring that scales

Keep pace with the flood of time series data. Learn how to build real-time monitoring that scales securely with InfluxDB and Grafana to keep ahead of outages, performance regressions, and costly blind spots.

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Deploy anywhere

On-prem, edge, or cloud. A single engine for every environment.

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Open and extensible

Integrate time series across AI/ML workloads & visualize instantly

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Code in the languages you love

Build and ship faster with client libraries

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Python

Javascript

Java

              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()
                  
                

                                    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()

                  
                

                                    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()
                  
                

                                    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()
                  
                

                                    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
}
                  
                

                                    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
}
                  
                

                                    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();
  }
}
                  
                

                                    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);
  }
}

                  
                

                                    package com.influxdb.v3;

import java.time.Instant;
import java.util.stream.Stream;

import com.influxdb.v3.client.InfluxDBClient;
import com.influxdb.v3.client.query.QueryOptions;
import com.influxdb.v3.client.Point;

public class IOxExample {
    public static void main(String[] args) throws Exception {
        String host = "https://us-east-1-1.aws.cloud2.influxdata.com";
        char[] token = "my-token".toCharArray();
        String database = "database";

        try (InfluxDBClient client = InfluxDBClient.getInstance(host, token, database)) {
            //
            // Query by SQL
            //
            System.out.printf("--------------------------------------------------------%n");
            System.out.printf("| %-8s | %-8s | %-30s |%n", "location", "value", "time");
            System.out.printf("--------------------------------------------------------%n");

            String sql = "select time,location,value from temperature order by time desc limit 10";
            try (Stream stream = client.query(sql)) {
                stream.forEach(row -> System.out.printf("| %-8s | %-8s | %-30s |%n", row[1], row[2], row[0]));
            }
            System.out.printf("--------------------------------------------------------%n%n");
        }
    }
}
                  
                

                                    package com.influxdb.v3;

import java.time.Instant;
import java.util.stream.Stream;

import com.influxdb.v3.client.InfluxDBClient;
import com.influxdb.v3.client.query.QueryOptions;
import com.influxdb.v3.client.Point;

public class IOxExample {
    public static void main(String[] args) throws Exception {
        String host = "https://us-east-1-1.aws.cloud2.influxdata.com";
        char[] token = "my-token".toCharArray();
        String database = "database";

        try (InfluxDBClient client = InfluxDBClient.getInstance(host, token, database)) {
            //
            // Write by Point
            //
            Point point = Point.measurement("temperature")
                   .setTag("location", "west")
                   .setField("value", 55.15)
                   .setTimestamp(Instant.now().minusSeconds(-10));
            client.writePoint(point);

            //
            // Write by LineProtocol
            //
            String record = "temperature,location=north value=60.0";
            client.writeRecord(record);
        }
    }
}
                  
                

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Client libraries

InfluxDB client libraries make it easy to integrate time series data into your applications using your favorite programming languages.

Community & ecosystem

InfluxDB includes a massive community of cloud and open source developers to help you work the way you want.

Time series starts with InfluxDB

Developers choose InfluxDB

Most databases weren’t built for time series