"DB Design Disaster: Can We Optimize This MySQL Schema for Scalability?"

[Jake105]

**Title:** DB Design Disaster: Can We Optimize This MySQL Schema for Scalability?

**My Post:**

Hey all, I'm looking for some help from the experts here. I'm currently working on a blockchain project that's experiencing some major scaling issues, and I think it's due to our MySQL schema being a hot mess. The schema I'm looking at has 17 tables, with 5 of them being huge with over 100,000 entries each - any tips on how to optimize this nightmare?

 

[ZAFAR]

"Hey OP, have you considered using NoSQL databases like MongoDB or Cassandra? They're more geared towards handling large amounts of data and can scale much better than traditional SQL ones like MySQL. Would love to see some data on the current schema's performance to help optimize."

 

[Pokotigoroh]

"Lately, I've been looking into using a document-based DB like MongoDB for high-traffic apps, seems like it simplifies a lot of the scaling pains of traditional relational DBs. Would love to see the schema and the queries you're running to see if there are any immediate wins. Maybe we can swap out some inefficient JOINs for some clever indexing?"

 

[Asus70]

"Lol, that schema does look messy. One thing that comes to mind is to consider sharding the user info into separate tables, could help with query performance and reduce load. Does anyone have experience with MariaDB, might be worth exploring those clustering features?"

 

[mutia]

"Dude, this schema looks like a mess. I'd recommend normalizing the tables and introducing a separate node for storing metadata. Have you considered using a NoSQL DB like MongoDB for this use case?"

 

[polzovatel]

"Lol, sounds like you've got a bit of a messy database on your hands. First thing to consider is normalizing those tables to reduce redundant data and make queries more efficient. Can you share some more details about your schema and what kind of queries you're running?"

 

[Dantee]

"Dude, have you considered adding more indexes to those queries that are taking ages? I'd also recommend looking into partitioning the tables by date to alleviate some of the load. Might also be worth exploring sharding, but that's a whole other story"