System Design Glossary

Object storage for unstructured binary data: images, videos, documents, ML model weights. Designed for durability and throughput at scale, not low-latency random access.

A distributed system can only guarantee two of three: Consistency, Availability, and Partition Tolerance.

Content Delivery Network. A geographically distributed network of edge servers that caches content close to end users, reducing origin server load and cutting time-to-first-byte by 50–200ms depending on user location.

A distributed hashing scheme that minimizes key remapping when nodes are added or removed.

Horizontal partitioning of a database across multiple machines to distribute load beyond a single server's capacity.

A shared cache layer across multiple nodes used to absorb read traffic from the primary database and reduce latency on hot data paths. The difference between a 2ms and a 200ms read at scale.

The problem of getting distributed nodes to agree on a single value despite network failures and partial outages. The theoretical foundation behind etcd, ZooKeeper, and Kafka leader election.

Numerical vector representations of text, images, or other data that encode semantic meaning. The translation layer that converts unstructured content into a form that can be compared mathematically.

Distributes incoming traffic across multiple servers to prevent any single node from becoming a bottleneck. The mechanism that makes horizontal scaling functional in practice.

Asynchronous communication buffer between services. Decouples producers from consumers and provides durability during traffic spikes.

Controls the rate of requests to a service. Common algorithms: Token Bucket, Leaky Bucket, Fixed Window, and Sliding Window.

A database purpose-built to store and query high-dimensional embedding vectors. The retrieval layer that makes semantic search and RAG pipelines possible at production scale.