How to load data from SFTP to Weaviate

Learn how to use Airbyte to synchronize your SFTP data into Weaviate within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a SFTP connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Weaviate for your extracted SFTP data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the SFTP to Weaviate in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync to Manually

Step 1: Access the SFTP Server

First, ensure that you have access credentials (hostname, username, password, or SSH key) to connect to the SFTP server. Use a command-line interface or an SFTP client to list the files you need to transfer. The command `sftp username@hostname` can be used to establish a connection. Use `ls` to list files and `cd` to navigate directories.

Once connected to the SFTP server, download the required data files to your local system. Use the `get` command followed by the filename to download individual files, or `mget` with wildcards (e.g., `mget *.csv`) to download multiple files at once. Ensure the files are saved in a directory where you have read and write permissions.

After downloading the data, inspect and prepare it for Weaviate ingestion. Weaviate typically requires data to be in JSON format with a schema that matches your Weaviate instance. Use a scripting language like Python to parse and convert your data (e.g., CSV to JSON) and ensure that it includes all necessary fields specified by your Weaviate schema.

If you don't have access to a hosted Weaviate instance, set up a local instance. You can do this by running Weaviate in a Docker container. Use the command `docker run -d -p 8080:8080 semi-technologies/weaviate:latest` to start the Weaviate server locally. Ensure that the Weaviate instance is running and accessible.

Before uploading data, ensure your Weaviate instance has the correct schema. Use Weaviate’s RESTful API to define classes and properties that match the data structure you prepared. Use `curl` commands or a tool like Postman to send HTTP requests to the Weaviate API endpoints to create the schema.

With the data prepared and the schema configured, upload the data to Weaviate. Write a script (using Python's `requests` library, for example) to send POST requests to the Weaviate `/v1/objects` endpoint. Iterate over your JSON data and send each item as a separate request. Handle responses to ensure data is uploaded successfully.

After uploading, verify that the data is correctly ingested into Weaviate. Use the Weaviate REST API to query the data and check their integrity and structure. Send a GET request to the `/v1/graphql` endpoint to perform queries and ensure that all data is present and accessible as expected.

By following these steps, you can manually transfer data from an SFTP server to Weaviate effectively, without relying on third-party connectors or integrations.