Handbook

Key technologies and patterns

Reference pages to read before an interview or while designing: what each tool is good at, how it works inside, and the standard answers to recurring problems.

Technologies

The building blocks interviewers expect you to know: what each is good at, how it works inside, and where it breaks.

In-memory storeRedisAn in-memory data structure server used as a cache, rate limiter, leaderboard, lock service, queue and pub/sub hub. What it's good at, how it scales, and where it bites. 10 min
Event logKafkaA distributed, partitioned, replicated log. How topics, partitions, replication and consumer groups work, the numbers to quote, and the design decisions that matter. 11 min
Relational databasePostgreSQLThe default relational database. Transactions and MVCC, indexes worth knowing, how far one node goes, and the ways to scale it. 11 min
Wide-column databaseCassandraA leaderless, wide-column database built for huge write volumes across many nodes and regions. Query-first data modeling, tunable consistency, and its sharp edges. 10 min
Managed key-value storeDynamoDBA fully managed key-value and document database with predictable single-digit-millisecond latency at any scale. Partition and sort keys, single-table design, indexes, capacity and its limits. 11 min
Search engineElasticsearchA distributed search and analytics engine built on inverted indexes. Indexing and analysis, relevance, shards and replicas, keeping it in sync, and running it well. 11 min
Object storageS3 and object storageCheap, durable storage for files of any size. Buckets and keys, durability and consistency, presigned and multipart uploads, storage classes, events and the limits that matter. 10 min
Coordination serviceZooKeeper and etcdSmall, strongly consistent stores for coordination. What they guarantee, leases and watches, leader election, service discovery and configuration, and what not to put in them. 10 min
Stream processorApache FlinkA stateful stream-processing engine for event-time windows, keyed aggregations and exactly-once guarantees. How watermarks, checkpoints and backpressure work, and when to choose Flink over Kafka Streams or Spark Streaming. 11 min
Edge layerAPI GatewaysThe single front door for a service fleet. Routing, authentication, rate limiting, TLS termination, request shaping, and aggregation. How gateways differ from load balancers and service meshes, and how to keep them from becoming a single point of failure. 10 min
Document storeMongoDBA document database storing flexible BSON records. When to embed vs reference, indexes, replica sets with elections, sharding mechanics, and write concerns. 11 min
Message queueSQS and RabbitMQMessage queues for point-to-point task distribution. Visibility timeouts, consumer acknowledgments, dead-letter queues, RabbitMQ exchange routing, and choosing between queues and logs. 11 min
Edge deliveryCDNs and Edge DeliveryContent delivery networks terminate TLS, cache static and dynamic assets at edge points of presence, and protect origins with shielding and signed URLs. 10 min
Columnar storeClickHouseA fast columnar analytical database for real-time aggregations over billions of events. The MergeTree engine family, columnar compression, vectorized execution, and batch ingestion. 12 min
Distributed SQLSpanner and CockroachDBGlobally distributed SQL databases providing serializable ACID transactions across multiple regions. Raft-replicated ranges, TrueTime vs hybrid logical clocks, and external consistency. 12 min
Traffic routingLoad BalancersDistributing network traffic across backend server pools. Layer 4 vs Layer 7 routing, balancing algorithms, health checks, connection draining, and load balancer redundancy. 11 min
Time-series storeTime-Series DatabasesStores optimized for timestamped metric and event streams. Data models, Gorilla and DoubleDelta compression, retention policies, downsampling rollups, cardinality explosion, and pull vs push collection. 11 min
Graph databaseGraph DatabasesSpecialized storage engines optimized for highly connected data and recursive graph traversals. Labeled property graphs, index-free adjacency, social relationships, fraud detection, graph sharding bottlenecks, and relational alternatives. 11 min
Vector databaseVector DatabasesSpecialized storage and approximate nearest neighbor (ANN) retrieval engines for dense embeddings. HNSW graphs, inverted file indexes (IVFFlat), recall versus latency trade-offs, pre-filtering challenges, pgvector vs dedicated stores, semantic search, and RAG architectures. 11 min

Patterns

Recurring problems in system design and the standard ways to solve them, with the trade-offs to talk through.