TL;DR

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

1. set up SFTP as a source connector (using Auth, or usually an API key)
2. set up Snowflake destination as a destination connector
3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is SFTP

SFTP (Secure File Transfer Protocol) is a secure way to transfer files between two computers over the internet. It uses encryption to protect the data being transferred, making it more secure than traditional FTP (File Transfer Protocol). SFTP is commonly used by businesses and organizations to transfer sensitive data such as financial information, medical records, and personal data. It requires authentication using a username and password or public key authentication, ensuring that only authorized users can access the files. SFTP is also platform-independent, meaning it can be used on any operating system, making it a versatile and reliable option for secure file transfers.

What is Snowflake destination

A cloud data platform, Snowflake Data Cloud provides a warehouse-as-a-service built specifically for the cloud. The Snowflake platform is designed to empower many types of data workloads, and offers secure, immediate, governed access to a comprehensive network of data. Snowflake’s innovative technology goes above the capabilities of the ordinary database, supplying users all the functionality of database storage, query processing, and cloud services in one package.

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Prerequisites

1. A SFTP account to transfer your customer data automatically from.
2. A Snowflake destination account.
3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including SFTP and Snowflake destination, for seamless data migration.

When using Airbyte to move data from SFTP to Snowflake destination, it extracts data from SFTP using the source connector, converts it into a format Snowflake destination can ingest using the provided schema, and then loads it into Snowflake destination via the destination connector. This allows businesses to leverage their SFTP data for advanced analytics and insights within Snowflake destination, simplifying the ETL process and saving significant time and resources.

Methods to Move Data From SFTP to snowflake

• Method 1: Connecting SFTP to snowflake using Airbyte.
• Method 2: Connecting SFTP to snowflake manually.

Method 1: Connecting SFTP to snowflake using Airbyte

Step 1: Set up SFTP as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Create a new connection" button and select "SFTP" as the source connector.
3. Enter a name for the connection and click "Next".
4. In the "Connection Configuration" section, enter the hostname or IP address of the SFTP server, as well as the port number (usually 22).
5. Enter the username and password for the SFTP server in the "Authentication" section.
6. If your SFTP server requires a private key for authentication, select the "Private Key" option and enter the path to the key file.
7. In the "Advanced" section, you can specify additional options such as the path to the remote directory and the file pattern to use for selecting files.
8. Click "Test" to verify that the connection is working correctly.
9. If the test is successful, click "Create" to save the connection and start syncing data from the SFTP server.

Step 2: Set up Snowflake destination as a destination connector

1. First, navigate to the Airbyte website and log in to your account.

2. Once you are logged in, click on the "Destinations" tab on the left-hand side of the screen.

3. Scroll down until you find the Snowflake Data Cloud destination connector and click on it.

4. You will be prompted to enter your Snowflake account information, including your account name, username, and password.

5. After entering your account information, click on the "Test" button to ensure that the connection is successful.

6. If the test is successful, click on the "Save" button to save your Snowflake Data Cloud destination connector settings.

7. You can now use the Snowflake Data Cloud destination connector to transfer data from your Airbyte sources to your Snowflake account.

8. To set up a data transfer, navigate to the "Sources" tab on the left-hand side of the screen and select the source you want to transfer data from.

9. Click on the "Create New Connection" button and select the Snowflake Data Cloud destination connector as your destination.

10. Follow the prompts to set up your data transfer, including selecting the tables or data sources you want to transfer and setting up any necessary transformations or mappings.

11. Once you have set up your data transfer, click on the "Run" button to start the transfer process.

Step 3: Set up a connection to sync your SFTP data to Snowflake destination

Once you've successfully connected SFTP as a data source and Snowflake destination as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
2. Choose your source: Select SFTP from the dropdown list of your configured sources.
3. Select your destination: Choose Snowflake destination from the dropdown list of your configured destinations.
4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
5. Select the data to sync: Choose the specific SFTP objects you want to import data from towards Snowflake destination. You can sync all data or select specific tables and fields.
6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from SFTP to Snowflake destination according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your Snowflake destination data warehouse is always up-to-date with your SFTP data.

Method 2: Connecting SFTP to snowflake manually

Moving data from an SFTP server to Snowflake without using third-party connectors or integrations involves several steps, including exporting data from the SFTP server, uploading it to a cloud storage service that Snowflake can access, and then copying the data into Snowflake. Below is a detailed step-by-step guide to accomplish this:

Step 1: Prepare the Data on SFTP Server

1. Log in to the SFTP server: Use an SFTP client or command-line tool to connect to the SFTP server with the appropriate credentials.

2. Locate the data files: Navigate to the directory where the data files you want to move are stored.

3. Export the data (if necessary): If the data isn't already in a flat-file format (CSV, JSON, etc.), export it to a format that Snowflake can ingest.

4. Compress the data (optional): To speed up the transfer, you can compress the data files using a tool like `gzip`.

Step 2: Transfer Data from SFTP to Cloud Storage

Snowflake can directly load data from cloud storage services like Amazon S3, Google Cloud Storage, or Azure Blob Storage. Choose the one that is most suitable for your Snowflake account and region.

If using Amazon S3:

1. Install AWS CLI: Install and configure the AWS Command Line Interface (CLI) with the necessary permissions to access your S3 bucket.

2. Upload to S3: Use the AWS CLI to upload the data files from your local machine to the appropriate S3 bucket using the `aws s3 cp` or `aws s3 sync` command.

If using Google Cloud Storage:

1. Install Google Cloud SDK: Install and configure the Google Cloud SDK with the necessary permissions to access your Cloud Storage bucket.

2. Upload to GCS: Use the `gsutil cp` command to upload the data files from your local machine to the appropriate Cloud Storage bucket.

If using Azure Blob Storage:

1. Install Azure CLI: Install and configure the Azure Command Line Interface (CLI) with the necessary permissions to access your Blob Storage container.

2. Upload to Blob Storage: Use the `az storage blob upload` command to upload the data files from your local machine to the appropriate Blob Storage container.

Step 3: Load Data into Snowflake

Once the data is in cloud storage, you can load it into Snowflake using the COPY INTO command.

1. Log in to Snowflake: Use the Snowflake web interface or a SQL client that supports Snowflake to log in to your account.

2. Create a File Format: Define a file format that matches the format of your data files:

   ```sql

   CREATE FILE FORMAT my_file_format

   TYPE = 'CSV'

   FIELD_DELIMITER = ','

   SKIP_HEADER = 1

   NULL_IF = ('\\N');

   ```

3. Create a Stage: Create a stage object that points to the location of the files in the cloud storage:

   ```sql

   -- For Amazon S3

   CREATE STAGE my_stage

   URL = 's3://mybucket/data/'

   FILE_FORMAT = my_file_format

   CREDENTIALS = (AWS_KEY_ID = 'my_aws_key_id' AWS_SECRET_KEY = 'my_aws_secret');

   -- For Google Cloud Storage

   CREATE STAGE my_stage

   URL = 'gcs://mybucket/data/'

   FILE_FORMAT = my_file_format

   CREDENTIALS = (GCS_CREDENTIALS = 'my_gcs_credentials_json');

   -- For Azure Blob Storage

   CREATE STAGE my_stage

   URL = 'azure://myaccount.blob.core.windows.net/mycontainer/data/'

   FILE_FORMAT = my_file_format

   CREDENTIALS = (AZURE_SAS_TOKEN = 'my_azure_sas_token');

   ```

4. Create a Target Table: Create a table in Snowflake to hold the data:

   ```sql

   CREATE TABLE my_table (

     column1 STRING,

     column2 STRING,

     ...

   );

   ```

5. Copy Data into Snowflake: Use the COPY INTO command to load the data from the stage into the Snowflake table:

   ```sql

   COPY INTO my_table

   FROM @my_stage

   FILE_FORMAT = (FORMAT_NAME = my_file_format);

   ```

6. Verify the Data Load: After the COPY INTO command completes, verify that the data has been loaded correctly:

   ```sql

   SELECT * FROM my_table LIMIT 10;

   ```

Step 4: Clean Up

After the data has been successfully loaded into Snowflake, you may want to clean up any temporary files or data that is no longer needed.

1. Remove Temporary Files: If you created any temporary files during the process, make sure to delete them from your local machine and cloud storage.

2. Close SFTP Connection: Log out from the SFTP server to ensure security.

3. Review Snowflake Costs: Loading data into Snowflake may incur costs, so review your usage and consider setting up resource monitors to manage expenses.

Remember to handle any sensitive credentials securely and to rotate them periodically. Also, consider automating this process for recurring data transfers using scripting and scheduling tools.

Use Cases to transfer your SFTP data to Snowflake destination

Integrating data from SFTP to Snowflake destination provides several benefits. Here are a few use cases:

1. Advanced Analytics: Snowflake destination’s powerful data processing capabilities enable you to perform complex queries and data analysis on your SFTP data, extracting insights that wouldn't be possible within SFTP alone.
2. Data Consolidation: If you're using multiple other sources along with SFTP, syncing to Snowflake destination allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: SFTP has limits on historical data. Syncing data to Snowflake destination allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: Snowflake destination provides robust data security features. Syncing SFTP data to Snowflake destination ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: Snowflake destination can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding SFTP data.
6. Data Science and Machine Learning: By having SFTP data in Snowflake destination, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While SFTP provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to Snowflake destination, providing more advanced business intelligence options. If you have a SFTP table that needs to be converted to a Snowflake destination table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a SFTP account as an Airbyte data source connector.
2. Configure Snowflake destination as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from SFTP to Snowflake destination after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!