Documentation

Python Flight client

Apache Arrow Python bindings integrate with Python scripts and applications to query data stored in InfluxDB.

Use InfluxDB 3 client libraries

We recommend using the influxdb3-python Python client library for integrating InfluxDB 3 with your Python application code.

InfluxDB 3 client libraries wrap Apache Arrow Flight clients and provide convenient methods for writing, querying, and processing data stored in InfluxDB 3 Core. Client libraries can query using SQL or InfluxQL.

The following examples show how to use the pyarrow.flight and pandas Python modules to query and format data stored in an InfluxDB 3 Core database:

# Using pyarrow>=12.0.0 FlightClient
from pyarrow.flight import FlightClient, Ticket, FlightCallOptions 
import json
import pandas
import tabulate

# Downsampling query groups data into 2-hour bins
sql="""
  SELECT DATE_BIN(INTERVAL '2 hours', time) AS time,
    room,
    selector_max(temp, time)['value'] AS 'max temp',
    selector_min(temp, time)['value'] AS 'min temp',
    avg(temp) AS 'average temp'
  FROM home
  GROUP BY
    1,
    room
  ORDER BY room, 1"""
  
flight_ticket = Ticket(json.dumps({
  "namespace_name": "
DATABASE_NAME
"
,
"sql_query": sql, "query_type": "sql" })) token = (b"authorization", bytes(f"Bearer
DATABASE_TOKEN
"
.encode('utf-8')))
options = FlightCallOptions(headers=[token]) client = FlightClient(f"grpc+tls://localhost:8181:443") reader = client.do_get(flight_ticket, options) arrow_table = reader.read_all() # Use pyarrow and pandas to view and analyze data data_frame = arrow_table.to_pandas() print(data_frame.to_markdown())
# Using pyarrow>=12.0.0 FlightClient
from pyarrow.flight import FlightClient, Ticket, FlightCallOptions 
import json
import pandas
import tabulate

# Downsampling query groups data into 2-hour bins
influxql="""
  SELECT FIRST(temp)
  FROM home 
  WHERE room = 'kitchen'
    AND time >= now() - 100d
    AND time <= now() - 10d
  GROUP BY time(2h)"""
  
flight_ticket = Ticket(json.dumps({
  "namespace_name": "
DATABASE_NAME
"
,
"sql_query": influxql, "query_type": "influxql" })) token = (b"authorization", bytes(f"Bearer
DATABASE_TOKEN
"
.encode('utf-8')))
options = FlightCallOptions(headers=[token]) client = FlightClient(f"grpc+tls://localhost:8181:443") reader = client.do_get(flight_ticket, options) arrow_table = reader.read_all() # Use pyarrow and pandas to view and analyze data data_frame = arrow_table.to_pandas() print(data_frame.to_markdown())

Replace the following:

  • DATABASE_NAME: your InfluxDB 3 Core database
  • DATABASE_TOKEN: a database token with sufficient permissions to the specified database

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InfluxDB 3.9: Performance upgrade preview

InfluxDB 3 Enterprise 3.9 includes a beta of major performance upgrades with faster single-series queries, wide-and-sparse table support, and more.

InfluxDB 3 Enterprise 3.9 includes a beta of major performance and feature updates.

Key improvements:

  • Faster single-series queries
  • Consistent resource usage
  • Wide-and-sparse table support
  • Automatic distinct value caches for reduced latency with metadata queries

Preview features are subject to breaking changes.

For more information, see:

Telegraf Enterprise now in public beta

Get early access to the Telegraf Controller and provide feedback to help shape the future of Telegraf Enterprise.

See the Blog Post

The upcoming Telegraf Enterprise offering is for organizations running Telegraf at scale and is comprised of two key components:

  • Telegraf Controller: A control plane (UI + API) that centralizes Telegraf configuration management and agent health visibility.
  • Telegraf Enterprise Support: Official support for Telegraf Controller and Telegraf plugins.

Join the Telegraf Enterprise beta to get early access to the Telegraf Controller and provide feedback to help shape the future of Telegraf Enterprise.

For more information:

Telegraf Controller v0.0.6-beta now available

Telegraf Controller v0.0.6-beta is now available with new features, improvements, and bug fixes.

View the release notes
Download Telegraf Controller v0.0.6-beta

InfluxDB Docker latest tag changing to InfluxDB 3 Core

On May 27, 2026, the latest tag for InfluxDB Docker images will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments.

If using Docker to install and run InfluxDB, the latest tag will point to InfluxDB 3 Core. To avoid unexpected upgrades, use specific version tags in your Docker deployments. For example, if using Docker to run InfluxDB v2, replace the latest version tag with a specific version tag in your Docker pull command–for example:

docker pull influxdb:2