Up to this point in the course you have studied data structures largely one at a time: a linked list here, a hash table there, a tree or graph in isolation. Real systems almost never work that way. A blockchain node, a payment network, or a social platform stitches several structures together — hash tables for fast lookup, linked structures for ordering and history, trees for verification, graphs for relationships — and layers them so that each structure handles the operation it is best suited for.
This topic asks you to think like a system designer rather than a single-structure implementer. Blockchain is our primary case study: hash-linked blocks, cryptographic digests, and Merkle trees combine to give immutability and efficient transaction verification, while hash tables and indexes make wallet balances and transaction lookups practical. Social and transactional networks give us a second case study, where the choice between adjacency lists and adjacency matrices, and between BFS and DFS traversal, directly changes storage cost and feature performance.
The three videos below come from ByteByteGo, a system design channel, and they frame the same question from an industry perspective: which structures, algorithms, and storage engines do large systems actually combine, and why. As you watch, keep a running list of the data structures mentioned, note the trade-off that justifies each one (time versus space, read speed versus write cost, simplicity versus scalability), and ask how you would describe that same decision using the formal cost analysis you have learned in this course.
A fast tour of core system design concepts that recur across large-scale applications — the kinds of building blocks (caching, indexing, replication, partitioning, and similar ideas) that engineers assemble when designing a service. The emphasis is on how these pieces fit together rather than on implementing any one of them in code.
It establishes the central premise of this topic — that complex systems are built by integrating multiple components and structures — and gives you industry vocabulary for discussing layered architecture and structural design decisions.
A survey of the algorithms and underlying data structures that commonly appear in system design discussions, presented in the context of real system components rather than textbook exercises. Expect coverage of techniques such as hashing and consistent hashing, tree- and trie-based indexing, and probabilistic or graph-related structures used at scale.
This is the closest fit to the topic's core question: it shows named data structures being selected for specific system roles, which supports the hash table, tree, and graph integration you are asked to reason about.
A walkthrough of how to choose among database types — relational, key-value, document, graph, and others — based on the shape of the data and the access patterns the application needs. The video frames the decision as a set of trade-offs rather than a single correct answer.
Database engines are data structures in production, so this video makes the trade-off reasoning concrete, including the case for graph stores when relationships dominate, as in social and transactional networks.
Together these videos supply the design-thinking frame that the module's case studies fill in with specifics. The algorithms video reinforces how hashing, trees, and graph-oriented structures are selected for particular roles, supporting your analysis of blockchain's hash-linked blocks and Merkle trees (MO1) and of digital currency platforms as integrated multi-structure systems (MO4). The database selection video models the explicit storage-versus-operation trade-off reasoning you will apply when justifying adjacency lists against adjacency matrices (MO2) and when choosing graph representations that make traversal-based features practical (MO3). The system design concepts video ties it all to layered architecture, preparing you to propose and defend your own multi-structure solution against stated performance and functional requirements (MO5). Note that none of the videos covers blockchain internals or BFS and DFS traversal directly — those come from the module readings and lectures; use the videos for the integration mindset and trade-off vocabulary.
These videos were chosen from YouTube on October 2, 2026. Each has captions; the player turns them on. Videos on YouTube can be changed or removed — if one no longer plays, tell your instructor. If a player does not appear, use its Watch on YouTube link.