Scaling Writes easy
Opening a new database connection for every write is expensive. What mechanism reuses existing open connections to improve throughput?
- A Data Replication.
- B Connection Pooling.
- C Sharding.
- D Caching.
Answer: B. Connection Pooling.
A Connection Pool keeps a 'pool' of live connections open. When a request comes in, it borrows a connection, uses it, and returns it to the pool, skipping the slow handshake process.
One system design question a day, with spaced repetition so the ones you miss come back.
Get the appRelated questions
- What does the 'Atomicity' property in a database transaction guarantee regarding writes?
- Your database is struggling with write traffic. You decide to 'Scale Up' (Vertical Scaling) by buying a bigger server. What is the eventual hard limit of this strategy?
- A developer sets up a 'Fire-and-Forget' write pattern (sending data without waiting for a database confirmation) to speed up the app. What is the major risk?
- Why is inserting 1,000 rows in a single 'Batch' query faster than executing 1,000 separate `INSERT` queries?
- In the Raft consensus algorithm, what mechanism prevents a 'Split Vote' (where no leader gets a majority) from stalling the cluster indefinitely?
- Your 'Logs' table has 10 billion rows and writes are getting slow. You barely access logs older than 1 year. What is the simplest strategy to improve performance?