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NEW InfluxDB 3.7 is now available for Core and Enterprise
Real-world AI starts with time series.
Time series starts with InfluxDB.
Join the millions of developers building real-time systems with InfluxDB, the leading time series database.
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Get started with InfluxDB 3 Enterprise
curl -O https://www.influxdata.com/d/install_influxdb3.sh && sh install_influxdb3.sh enterpriseCopy
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Time series database
Source: DB Engines
Why InfluxDB
Manage high-volume, high-velocity data without sacrificing performance.
High-performance at scale
Manage millions of time series data points per second without limits or caps.
Run where you need it
Run at any scale in any environment: in the cloud, on-prem, or at the edge.
Build with the tools you love
Easily connect to your tech stack using data standards and 5K+ easy integrations.
InfluxDB is the engine behind the real-time data pipeline.
Real-time AI requires massive streams of time series. This allows data to flow continuously through ingest, analysis, compression, and integration—fueling smarter, more autonomous systems.
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.
Energy & Utilities
Power modern energy systems with real-time insights that maximize efficiency and reduce downtime.
Modern Data Historian
Upgrade your historian for Industry 4.0 with real-time data that drives efficiency and lowers costs.
Physical AI runs on time series
Predict the future based on the past.
InfluxDB captures high-resolution time series data with the precision and context AI models need to infer cause and effect, enabling real-time systems to detect, respond, and predict intelligently.
Anomaly Detection
Find failure fast—detect anomalies in real-time, trigger automated responses, and adapt as conditions change.
Predictive Maintenance
Prevent downtime before it hits. Monitor equipment health and usage patterns to predict issues and resolve them before they start.
Autonomous Optimization
Build self-correcting systems. Enable models to self-learn and adapt through continuous retraining—automatically.
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.
Deploy anywhere
Whether you’re building on-prem, in a private or multi-tenant cloud, or at the edge, InfluxDB meets developers where they are.
Start Testing See ways to get started
Open and extensible
Ingest from anywhere, deploy your way, and integrate with everything in your stack.
Code in the languages you love
Python
Javascript
Go
C#
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
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 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
300+ Telegraf plugins
Integrate your favorite tools with Telegraf, our popular open source connector with 5B+ downloads.
Client libraries
InfluxDB client libraries make it easy to integrate time series data into your applications using your favorite programming languages.
Community and ecosystem
InfluxDB includes a massive community of cloud and open source developers to help you work the way you want.
By developers, for developers
Connect with the InfluxDB developer community.
InfluxDB is a G2 Leader in Time Series
“InfluxDB is a strong database built specifically for time series data. It has made working with such data seamless and easy.”
— Verified G2 reviewer
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