I Built an LSM-Tree in Pure Python and Finally Understood How RocksDB and Cassandra Handle Millions of Writes

1. 1Build a write-ahead log to handle sequential writes
2. 2Implement a bloom filter to reduce disk reads
3. 3Design an LSM-Tree data structure to manage disk storage
4. 4Configure the LSM-Tree to handle compaction and merging
5. 5Test the LSM-Tree with a high-volume write workload
6. 6Optimize the LSM-Tree for better performance and scalability

Database engineers and software developers can benefit from understanding LSM-Tree architecture to improve database performance and scalability

💡 LSM-Trees use a combination of in-memory and disk storage to achieve high write throughput and low latency

💡 Built an LSM-Tree in Python to understand how RocksDB & Cassandra handle millions of writes