LSM-Trees vs B-Trees

Log-Structured Merge-Trees optimize for ultra-high write throughput by appending mutations to an in-memory MemTable, flushed sequentially to immutable disk SSTables.

STAFF ENGINEER TAKEAWAY: B-Trees optimize for fast reads with random in-place updates; LSM-Trees turn random writes into fast sequential disk I/O, using Bloom filters to speed up reads.

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More Topics in 3. Data & Storage

🗄️SQL Relational vs NoSQL Engines

SQL databases enforce structured schemas and ACID transactions with relations. NoSQL systems optimize for flexible schemas, horizontal partition scale, and eventual consistency.

🌲B-Tree & B+Tree Indexing

Self-balancing search tree data structure that keeps data sorted and allows searches, sequential access, insertions, and deletions in logarithmic O(log N) time.

🏛️ACID Transactions & Isolation Levels

Guarantees Atomicity (all-or-nothing), Consistency (rules preserved), Isolation (concurrent safety), and Durability (WAL commits survive power loss).

🔺CAP Theorem (Consistency vs Availability)

In any distributed data store, network partitions (P) are inevitable. When a partition occurs, the system must choose between Consistency (CP) or Availability (AP).