Why is Notion slow with large databases?

Notion's performance degrades significantly with large databases due to fundamental architectural constraints in how it stores and processes data. Unlike traditional database applications, every element in Notion—from text blocks to database entries—is stored as individual "blocks" in a centralized PostgreSQL database, which creates exponentially more data overhead as your workspace grows. Performance issues typically become noticeable around 10,000-20,000 database rows, with severe slowdowns occurring beyond this threshold as the system struggles to process the complex web of interconnected blocks that make Notion so flexible.

The root cause lies in Notion's block-based architecture, which prioritizes flexibility over raw performance. When you create a database entry, it's not just a single row like in traditional databases—it's composed of multiple blocks representing each property, relationship, and piece of content. This means a 20,000-row database might actually contain hundreds of thousands of individual blocks that need to be queried, synchronized, and rendered. As Notion's engineering team discovered, their system began experiencing serious performance degradation after reaching approximately 20 billion blocks globally, forcing them to implement complex database sharding across hundreds of servers.

Several specific factors compound these slowdowns in your day-to-day usage. Complex operations like filtering, sorting, and calculating rollups require intensive computational processing, especially when dealing with formula fields or text-based searches. The more properties you display in a database view, the larger the data payload that needs to be transferred and rendered in your browser. Real-time collaboration features also add overhead, as Notion constantly synchronizes block changes across all users viewing the same content.

Client-side limitations further impact performance when working with large databases. Your browser must process and render thousands of block objects simultaneously, which can overwhelm typical device memory and processing capabilities. This explains why you might experience browser freezing or extended loading times when opening large database views, particularly on less powerful devices.

While these architectural constraints create genuine performance challenges, they're the trade-off for Notion's remarkable flexibility and real-time collaboration capabilities. Understanding these limitations helps you optimize your workspace structure—consider breaking large databases into smaller, related ones, limiting visible properties in views, and simplifying complex formulas where possible. Though Notion continues improving its infrastructure through better sharding and optimization, the fundamental block-based architecture means performance considerations will always be part of working with large-scale data in the platform.