Big Binary Files Upload (PostgreSQL)

👉 Overview

👀 What ?

The topic at hand is the upload of big binary files using PostgreSQL, a powerful, open-source object-relational database system. Big binary files are large data files that are read in binary mode, which is the computer's native format of ones and zeros.

🧐 Why ?

The importance of this topic lies in its relevance to today's data-driven world. With the exponential growth of data, it becomes critical to manage and handle large files efficiently. Uploading big binary files in PostgreSQL can pose a challenge due to memory constraints, network bandwidth, and the time required for upload. It is essential to understand this topic to optimize the process and maintain data integrity.

⛏️ How ?

To upload a big binary file in PostgreSQL, you can use the Large Object feature. Large Objects are like normal PostgreSQL data types, but they are stored in a special format that allows efficient streaming access. Here are the steps: \n1. Create a Large Object: SELECT lo_creat(-1); \n2. Open the Large Object: SELECT lo_open(oid, mode); \n3. Upload the file: lo_put(oid, offset, buffer); \n4. Close the Large Object: SELECT lo_close(fd); \nRemember, these steps should be performed inside a transaction block to ensure data consistency.

⏳ When ?

The usage of PostgreSQL for managing and handling big binary files became more prevalent with the advent and growth of Big Data. As companies started to generate massive amounts of data, the need for efficient storage and handling mechanisms grew, leading to the adoption of technologies like PostgreSQL.

⚙️ Technical Explanations

PostgreSQL uses the TOAST (The Oversized-Attribute Storage Technique) to automatically store large data values in a separate area, allowing efficient handling of large data. It compresses the large values (if possible) and stores them out of the main table. Large Object, on the other hand, allows efficient streaming access to the data. It splits the data into chunks, allowing you to fetch or modify a part of the data without needing to access the whole. This makes it ideal for handling big binary files.