LSM Trees Explained: Powering Cassandra, RocksDB, HBase

🔥 Discover Log-Structured Merge Trees (LSM Trees) – the storage engine behind Cassandra, RocksDB, and HBase! 🚀

Learn how LSM Trees handle MILLIONS of writes per second through sequential I/O, MemTables, SSTables, and smart compaction strategies. Perfect for write-heavy distributed databases! 💾

From the write path to leveled vs tiered compaction, this deep dive covers:
• Why B-Trees fail at high write throughput
• MemTable → SSTable flush process
• Bloom filters & read optimizations
• Leveled, Tiered, Size-Tiered compaction
• Real-world implementations

Ideal for developers building scalable systems! 🛠️

#LSMTree #DistributedSystems #Cassandra #RocksDB #HBase #DatabaseEngineering #NoSQL

Chapters:
00:00 - Log-Structured Merge Trees
00:34 - The Problem: Write-Heavy Workloads
01:30 - LSM Tree Core Architecture
02:32 - Write Path in LSM Trees
03:37 - Read vs Write Trade-off
04:56 - Optimizing Read Performance
06:09 - Compaction: The Key Process
07:17 - Compaction Strategies
08:33 - LSM Trees in Production
09:36 - Key Takeaways & Trade-offs
10:41 - Outro

🔗 Stay Connected:
▶️ YouTube: https://youtube.com/@thecodelucky
📱 Instagram: https://instagram.com/thecodelucky
📘 Facebook: https://facebook.com/codeluckyfb
🌐 Website: https://codelucky.com

⭐ Support us by Liking, Subscribing, and Sharing!
💬 Drop your questions in the comments below
🔔 Hit the notification bell to never miss an update

#CodeLucky

Видео LSM Trees Explained: Powering Cassandra, RocksDB, HBase канала CodeLucky