How to load data from SFTP to Kafka
Learn how to use Airbyte to synchronize your SFTP data into Kafka within minutes.


Building your pipeline or Using Airbyte
Airbyte is the only open source solution empowering data teams to meet all their growing custom business demands in the new AI era.
Building in-house pipelines
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
After Airbyte
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes



Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
Simple & Easy to use Interface
Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.
Guided Tour: Assisting you in building connections
Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.
Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes
Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.
What sets Airbyte Apart
Modern GenAI Workflows
Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.
Move Large Volumes, Fast
Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.
An Extensible Open-Source Standard
More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.
Full Control & Security
Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.
Fully Featured & Integrated
Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.
Enterprise Support with SLAs
Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.
What our users say

Raman Singh
Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

Chase Zieman

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

Rupak Patel
"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."
How to Sync to Manually
Step 1: Set Up SFTP Client
Start by setting up an SFTP client on your server or local machine. You can use programming libraries such as `paramiko` in Python to connect to the SFTP server. This will allow you to authenticate and establish a connection to download the necessary files.
Step 2: Download Files from SFTP
Use the SFTP client to list and download the files from the SFTP server. Ensure you handle exceptions and possible errors, such as network issues or authentication failures. You might want to implement a mechanism to track already downloaded files to avoid duplicates.
Step 3: Set Up a Kafka Producer
Install and configure a Kafka producer in the programming language of your choice. Kafka provides client libraries in multiple languages such as Java, Python, and Go. This producer will be responsible for sending your data to Kafka topics.
Step 4: Read and Process Data
Once the files are downloaded from SFTP, read the data and prepare it for sending to Kafka. Depending on the file format (e.g., CSV, JSON, XML), you may need to parse and transform the data. Ensure the data structure matches the Kafka topic schema.
Step 5: Send Data to Kafka Topic
With the Kafka producer set up and data processed, send the data to the appropriate Kafka topic. Make sure you handle potential issues, such as retries on failure or message acknowledgment confirmations, to ensure data is reliably sent.
Step 6: Monitor and Log the Process
Implement logging to monitor the data transfer process from SFTP to Kafka. This will help in identifying any issues quickly and provide a record of successful data transfers. Logs should include details such as timestamps, file names, sizes, and any errors encountered.
Step 7: Schedule Regular Transfers
Use a scheduling tool like cron (on UNIX-based systems) or Task Scheduler (on Windows) to automate the process at regular intervals. This ensures that new data from the SFTP server is consistently moved to Kafka without manual intervention, maintaining up-to-date data flow.
By following these steps, you will build a custom data pipeline from SFTP to Kafka without relying on third-party connectors or integrations.