Feel the tradeoffs.
Don't just read about them.

Interactive visualizations that let you play with distributed systems concepts. Drag sliders, click buttons, watch data flow — and finally understand why things break.

🔷 TiDB / Database Internals

✦ Live

Raft Region Size

The invisible lever for performance & recovery
✦ Live

LSM-Tree & Compaction

How TiKV stores data and manages write amplification
✦ Live

Distributed Transactions

Percolate 2PC: prewrite, commit, and lock resolution
Coming soon

Hot Regions & Load Balancing

PD scheduler: splitting, scattering, and rebalancing
Coming soon

TiFlash HTAP

Row store vs column store, when to use each
Coming soon

Coprocessor Push-Down

Moving computation to storage nodes
Coming soon

GC & MVCC

Multi-version concurrency and garbage collection
Coming soon

Backup & PITR

Full backups, incremental, and point-in-time recovery

🍃 MongoDB

✦ Live

Sharding & Chunks

How data distributes across shards — and how to avoid hotspots
Coming soon

WiredTiger Storage

The engine behind MongoDB's performance
Coming soon

Replica Set Elections

Leader election and failover mechanics

📨 Apache Kafka

✦ Live

Partitions & Offsets

The anatomy of a Kafka topic — and how to choose partition counts
Coming soon

ISR & Replication

In-sync replicas and durability guarantees
Coming soon

Log Compaction

Keeping the latest value per key

⚡ Apache Spark

✦ Live

DAG Execution

Stages, tasks, and the execution plan — plus tuning for performance
Coming soon

Shuffle Internals

The most expensive operation in Spark