How to load data from SFTP Bulk to Postgres destination

Learn how to use Airbyte to synchronize your SFTP Bulk data into Postgres destination within minutes.

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a SFTP Bulk connector in Airbyte

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

Set up Postgres destination for your extracted SFTP Bulk 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 Bulk to Postgres destination 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: Set Up SSH Access

First, ensure you have SSH access to the SFTP server. You need the server's IP address, username, and password or SSH key. Test your access using an SSH client (like OpenSSH) by running:
```bash
ssh user@server_ip
```
This step ensures you can connect and navigate the SFTP server.

Step 2: Locate and Download the Data Files

Use the SFTP command-line tool to locate and download the files. Start an SFTP session and navigate to the directory containing the data files:
```bash
sftp user@server_ip
sftp> cd /path/to/data/files
sftp> lcd /local/path/to/store/files
sftp> mget
```
This will download all files from the specified directory on the SFTP server to your local machine.

Step 3: Prepare Local Environment for Data Processing

Ensure you have the necessary tools to process the data on your local machine. This typically involves having a scripting language like Python or Bash installed. For example, you can use Python's built-in CSV module to read and process CSV files.

Step 4: Data Transformation and Cleaning

Process the downloaded files to ensure they are in a format suitable for PostgreSQL. This might involve cleaning the data, handling missing values, or converting data types. Here's a simple Python script example:
```python
import csv

def clean_data(file_path):
with open(file_path, 'r') as infile, open('cleaned_data.csv', 'w', newline='') as outfile:
reader = csv.reader(infile)
writer = csv.writer(outfile)
for row in reader:
# Perform any necessary data cleaning
writer.writerow(row)

clean_data('/local/path/to/store/files/data.csv')
```

Step 5: Set Up PostgreSQL Credentials and Access

Ensure you can access the PostgreSQL database. You need the database host, port, username, password, and database name. Test your connection with a tool like psql:
```bash
psql -h db_host -U db_user -d db_name
```
This verifies that you can connect to the database where you will upload the data.

Step 6: Create Tables in PostgreSQL

Before uploading, ensure the PostgreSQL database has the necessary tables to receive the data. Use SQL commands to create tables as needed:
```sql
CREATE TABLE my_table (
column1 datatype,
column2 datatype,
...
);
```
Adjust the table structure based on the data you plan to import.

Step 7: Insert Data into PostgreSQL

Load the cleaned data into PostgreSQL. You can use the `COPY` command or a scripting language like Python with a library such as psycopg2:
```python
import psycopg2

conn = psycopg2.connect("dbname=db_name user=db_user password=db_pass host=db_host")
cur = conn.cursor()
with open('cleaned_data.csv', 'r') as f:
cur.copy_expert("COPY my_table FROM STDIN WITH CSV HEADER", f)
conn.commit()
conn.close()
```
This imports the data from the cleaned CSV file into the specified PostgreSQL table.

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