Storing PDF and DOC files in databases is a common requirement in enterprise software, legal platforms, HR systems, and content management solutions. Whether you’re using MySQL, PostgreSQL, or MongoDB, the key lies in how your chosen programming language processes files into a format that the database can store efficiently and reliably.

In my 20-year tech career, I’ve been a catalyst for innovation, architecting scalable solutions that lead organizations to extraordinary achievements. My trusted advice inspires businesses to take bold steps for usage of future ready technology. In this tech concept, we explore how popular languages like Python, Java, Node.js, PHP, and C# handle PDF and DOC files for database storage, and how they interact with different database systems.

Core Workflow: How File Storage Works Across Languages

Regardless of language, the high-level process of storing a file (PDF/DOC) in a database typically follows these steps:

1. Read the file in binary mode
2. Convert the file into a byte array or buffer
3. Format the binary data to match the target database’s requirements
4. Insert the file along with metadata like filename, MIME type, and timestamps

Let’s explore how various programming languages handle this workflow, and the database-specific techniques they use.

Python

File Handling Concept

• Use open(file, "rb") to read the file as binary.
• Store the resulting bytes object into the database using appropriate driver methods.

PDF/DOC File Processing

• Use PyPDF2 or pdfplumber for PDF content inspection (optional).
• Use python-docx for DOCX content parsing if needed.

Database Techniques

• MySQL: Use mysql-connector-python to insert bytes into a LONGBLOB field.
• PostgreSQL: Use psycopg2 with psycopg2.Binary() for BYTEA fields.
• MongoDB: Use pymongo, wrap binary with bson.Binary() or use GridFS for large files.

Java

File Handling Concept

• Use FileInputStream to read files as byte[].
• Use JDBC’s PreparedStatement.setBinaryStream() or setBytes() for safe insertion.

PDF/DOC File Processing

• Use Apache PDFBox for PDFs and Apache POI for Word documents if content processing is required.

Database Techniques

• MySQL: Use JDBC with setBinaryStream() to insert into BLOB fields.
• PostgreSQL: Use setBytes() or stream with large object APIs.
• MongoDB: Use MongoDB Java Driver; wrap binary with Binary or use GridFSBucket for large files.

Node.js (JavaScript/TypeScript)

File Handling Concept

• Use Node’s fs.readFile() or fs.createReadStream() to handle files as Buffer.

PDF/DOC File Processing

• Use libraries like pdf-parse, pdfjs-dist for PDFs or mammoth for DOCX (optional for parsing, not needed for storage).

Database Techniques

• MySQL: Use mysql2, send buffer data into LONGBLOB using prepared queries.
• PostgreSQL: Use pg and send Buffer to BYTEA field.
• MongoDB: Use native MongoDB driver with Buffer or GridFS for files >16MB.

PHP

File Handling Concept

• Use fopen($file, "rb") with fread() to read file into a binary string.
• Use base64_encode() if required for transport or MongoDB insertion.

PDF/DOC File Processing

• Use TCPDF or DOMPDF for PDF files, and PhpWord for DOCX content if processing is required.

Database Techniques

• MySQL: Use PDO with bindParam() and LOB to insert BLOB data.
• PostgreSQL: Use pg_escape_bytea() and pg_query_params() for inserting binary data.
• MongoDB: Use the official MongoDB PHP library and GridFS for large files.

C# (.NET)

File Handling Concept

• Use File.ReadAllBytes(filePath) to obtain a byte[].

PDF/DOC File Processing

• Use libraries such as PdfSharp, iTextSharp, or Aspose.PDF for PDF.
• Use OpenXML SDK or Aspose.Words for DOCX file processing.

Database Techniques

• MySQL/PostgreSQL: Use ADO.NET or Entity Framework with SqlParameter to store into BLOB or BYTEA.
• MongoDB: Use the MongoDB C# Driver with GridFSBucket.UploadFromBytes() for storing large files.

Database-Specific Considerations Across Languages

MySQL

• Use BLOB family types (TINYBLOB, BLOB, MEDIUMBLOB, LONGBLOB) depending on file size.
• Use prepared statements for binary-safe insertion.
• Consider tuning max_allowed_packet for large files.

PostgreSQL

• Use BYTEA for small to medium files (up to a few MB).
• Use Large Objects (lo) and OID references for bigger files.
• Wrap binary data with pg_escape_bytea() or client-specific wrappers.

MongoDB

• Use BinData for files under 16MB.
• Use GridFS for files exceeding 16MB or when partial streaming is needed.
• All official drivers support GridFSBucket for large files.

Summary: File Storage Techniques by Language and Database

My Tech Advice: Each language provides simple mechanisms to read files and convert them into binary formats that can be inserted into relational or NoSQL databases. Understanding how your language interacts with the database enables you to build robust and efficient file storage capabilities directly in your applications.

• Use MySQL for simplicity and small-to-medium binary files.
• Use PostgreSQL when you require advanced binary handling or large object support.
• Choose MongoDB with GridFS for flexible handling of large and streamable files.

Ready to build your own tech solution ? Try the above tech concept, or contact me for a tech advice!

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Note: The names and information mentioned are based on my personal experience; however, they do not represent any formal statement.

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