In Memory Database
An in-memory database keeps the working set in RAM for sub-millisecond reads/writes, typically adding durability via logs/snapshots and HA via replication/sharding.
Amazon DynamoDB
Fully managed NoSQL database service designed for high performance at any scale
B-Trees vs LSM-Trees
Comparing write-optimized LSM-trees with read-optimized B-trees for database storage
Bloom Filters
A space-efficient probabilistic data structure that tests whether an element is a member of a set — with possible false positives but never false negatives
Column-Oriented Storage
How columnar storage optimizes analytical workloads and compression
Distributed Join Algorithms
Sort-merge, hash, and broadcast joins in distributed systems
In-Memory Databases
Benefits and challenges of keeping entire datasets in RAM
Isolation Levels
Read uncommitted, committed, repeatable read, and serializable isolation levels
MVCC (Multi-Version Concurrency Control)
How databases provide isolation without locking
Rate Limiting
Controlling the rate of requests to protect systems from overload and ensure fair usage
Rebalancing Partitions
Redistributing data when adding or removing nodes
Serialization Formats Comparison
JSON vs Protocol Buffers vs Avro vs Thrift - choosing the right format
Understanding Rust's Memory Safety Guarantees
Deep dive into how Rust prevents memory bugs at compile time through ownership, borrowing, and lifetimes.