How would you design the data structures for a social network (Social Graph)?

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Accepted Answer

## Step 1: Use Cases, Constraints, Assumptions, Back-of-Envelope

### Use cases
We'll scope to handle only the core flows that expose the bottlenecks; everything else is deferred.

- **User** adds/removes friend — mutual edge write, idempotent, replicated with quorum.
- **User** reads friends / friends-of-friends — adjacency lookup, paginated, filtered by activity.
- **User** reads feed derived from graph — 2-hop traversal (friends' posts) with cache.
- **Service** suggests friends — FoF (friend-of-friend) ranking via mutual count.

### Out of scope
- Messaging, media posts themselves, auth, privacy ACL beyond edge visibility (separate policy engine).

### State assumptions
- 500M users, avg 200 friends → 100B edges (undirected stored as 2 directed =200B rows).
- Edge 16 bytes (2*8) + overhead 32B ≈ 48B → 200B*48≈9.6 TB raw, 30 TB with replicas+indexes.
- Read QPS: friend-list 10k/s, FoF 1k/s, feed-by-graph 5k/s; Write QPS: add friend 500/s.
- Need <50ms friend lookup p95, <300ms FoF,

How would you design the data structures for a social network (Social Graph)?

Understand the problem

Attempt it yourself

Study the solution

Step 1: Use Cases, Constraints, Assumptions, Back-of-Envelope

Use cases

Solution ready — 2 min read

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Understand the problem

Attempt it yourself

Study the solution

Step 1: Use Cases, Constraints, Assumptions, Back-of-Envelope

Use cases

Solution ready — 2 min read

Join the discussion

Discussion (0)

KEEP THESTREAK ALIVE.

KEEP THE
STREAK ALIVE.