- Intermediate
- Data and storage
Where it shows up in real systems
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Key-value store
Data is spread across partitions by the hash of its key, so throughput scales almost without limit as long as keys are well distributed. A single very popular key hits one partition's limit and gets throttled. On-demand mode follows traffic but absorbs sudden jumps above twice the previous peak with throttling.
In production: Amazon DynamoDB, Azure Cosmos DB, Google Bigtable, Riak, FoundationDB
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Document database
A replica set elects a new primary when the current one fails. With write concern majority, an acknowledged write survives that failover; with w:1, recent writes can be rolled back. Reading from secondaries scales reads but returns slightly stale data.
In production: MongoDB Atlas, Amazon DocumentDB, Couchbase, Firestore
See it break, then fix it
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