Latest articles, tutorials, and deep dives from ndlab tech blog.
CAP theorem is misunderstood constantly. PACELC is more useful but almost unknown. This post explains both with concrete database examples and the decisions they actually inform.
Sharding splits data across multiple nodes and creates a new class of problems. This post covers range, hash, and consistent hashing with trade-offs that matter in production.
Automatic failover sounds simple — consensus makes it hard. This post explains leader election, Raft vs Paxos trade-offs, and what high availability means in distributed databases.
Replication lag creates bugs that only appear under load. Read-your-own-writes, monotonic reads, and consistent prefix reads are the guarantees that prevent them.
Replication keeps databases available when servers fail. Single-leader, multi-leader, and leaderless each trade consistency differently — this post explains all three clearly.
How does a database survive a server crash without losing data? The Write-Ahead Log is the answer. This post explains WAL, ARIES recovery, and what durability actually guarantees.
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