Kestra for
Data Engineers

Orchestrate your Data Pipelines, Automate Processes, and Harness the Power of Your Data

Talk to Us Get started

Simplify Your
Data Engineering Challenges

From automating data pipelines to accelerating machine learning model deployment, Kestra streamlines complex workflows across a wide range of industries and domains. Dive into the wide array of use cases Kestra efficiently addresses.

01

Automate Your Data Pipelines

Say goodbye to delays in your pipeline as Kestra initiates workflows based on specific times or events, such as data arrivals or file uploads.

02

Deploy Machine Learning Models

Efficiently manage and deploy machine learning models at scale using Kestra’s orchestration capabilities.

03

Optimize ETL Processes

Move, prepare, and clean data, consolidating it into a single data mart for easy access.

04

Seamless Data Integration

Easily connect and integrate with various data sources, ensuring smooth data flow across your systems.

05

Real-time Data Processing

Automatically detect and process changes in data sources with change data capture, keeping your data up-to-date and accurate.

06

Automated Reporting

Configure Kestra to distribute reports via email or Slack, keeping your team informed.

07

Efficient Data Scraping

Easily collect data from various sources and integrate it into your workflows.

08

End-to-End Data Orchestration

Manage the entire data lifecycle, from ingestion to reporting, with Kestra’s powerful orchestration capabilities.

Explore Blueprints

data
Airbyte Cloud ingestion with dbt Cloud transformation
data
Trigger multiple Airbyte Cloud syncs in parallel, then run a dbt job
data
Trigger a single Airbyte Cloud sync on schedule
data
Trigger multiple Airbyte syncs, then run a dbt job
data
Trigger multiple Airbyte syncs in parallel
data
Extract data, transform it, and load it in parallel to S3 and Postgres — in less than 7 seconds!
data
Extract data from a REST API, process it in Python with Polars in a Docker container, then run DuckDB query and preview results as a table in the Outp...
data
Azure Blob Storage file detection event triggers upload to BigQuery and dbt Cloud job
coredata
Cache a computationally expensive task in an ETL pipeline using the taskCache property
data
Extract data from Cassandra into a CSV file, and load it to BigQuery
aidata
Chat with your Elasticsearch data using the OpenAI plugin (RAG)
clouddata
Orchestrate CloudQuery data ingestion syncs to integrate data about your AWS resources into Postgres and and analyze it in SQL
data
Schedule a CloudQuery data ingestion sync with kestra
data
Load a CSV file to a Postgres table
data
Fetch data from Couchbase and transform it with Pandas in Python
data
Query a CSV file with DuckDB and send results via Slack every Monday
getting-startedcoredata
Getting started with Kestra — a Data Engineering Pipeline example
data
Run a SQL query on Databricks, output the result to a CSV file and read that CSV file in a Python script with Pandas
data
Git workflow for dbt with Google BigQuery
data
Git workflow for dbt with DuckDB
data
Run dbt CLI commands in one container: dbt deps & dbt build
data
Git workflow for dbt with MotherDuck
data
Git workflow for dbt with Postgres
data
Git workflow for dbt with Amazon Redshift
data
Git workflow for dbt with Snowflake

Kestra's Capabilities
for Data Orchestration

Change data capture

Change data capture

Streamline Complex Data Pipelines and Automate Repetitive Tasks for Enhanced Efficiency

Data Stack

Modern Data Stack Integration

Integrate leading data tools from the Modern Data Stack with Kestra

CI/CD

CI/CD for your Kestra Workflows

Embrace software engineering practices for versioning, deploying, and maintaining data workflows

Take Kestra to the next level with the Enterprise Edition

Ensure scalability and high availability with managed Kafka and Elasticsearch integrated into the Enterprise Edition to eliminate single point of failure.

Learn more Get a demo