I’m trying to figure out the best way to set up a database for a system that lets users create and edit content in blocks. These blocks can contain different types of content and even other blocks inside them. The system should save changes automatically and show updates to other users right away.
I’m not sure if I should use references between blocks or store all the data in one place. Using references might mean more trips to the database, but storing everything together could get messy if the blocks are nested deep.
Has anyone built something like this before? What worked well? I’d love to hear about your experiences or any tips you might have. Thanks!
I’ve actually worked on a similar system before, and we found that using a hybrid approach worked best for us. We used a combination of relational and document-based storage.
For the basic block structure, we used a relational database with tables for blocks, content types, and user permissions. This allowed for efficient querying and maintaining relationships between blocks.
However, for the actual content within blocks, we used a document store (MongoDB in our case). This gave us the flexibility to handle different content types and nested structures without having to constantly alter table schemas.
To handle real-time updates, we implemented a pub/sub system using Redis. When a block was updated, we’d publish the change, and connected clients would receive the update almost instantly.
One challenge we faced was managing concurrency when multiple users were editing the same block. We ended up using optimistic locking with version numbers to handle this.
Performance-wise, this setup worked well for us, even with deeply nested structures. The key was to optimize our queries and use caching strategically. Hope this helps give you some ideas for your own implementation!
Having implemented a similar system, I can share some insights. We opted for a graph database (Neo4j) which proved excellent for handling complex relationships between blocks. This approach allowed for efficient querying of nested structures and simplified the process of rearranging content hierarchies.
For real-time collaboration, we utilized WebSockets coupled with a message queue (RabbitMQ) to propagate changes instantly. This setup ensured that all connected clients received updates promptly without overwhelming our servers.
To manage concurrent edits, we implemented operational transformation, which allowed multiple users to edit simultaneously without conflicts. This was crucial for maintaining data integrity in a collaborative environment.
One challenge we encountered was optimizing for large-scale operations, like bulk imports or global changes. We addressed this by implementing background jobs for heavy operations, ensuring the system remained responsive for regular users.
yo, i built smth similar using postgres w/ jsonb. it’s pretty flexible for nested stuff. we used redis for real-time updates, worked great. one tip: cache frequently accessed blocks to avoid hitting db too much. also, implement version control - saved our butts many times. good luck w/ ur project!