Vibgrate Graph Performance and Incremental Builds

Vibgrate Graph is designed to stay fast even on large codebases. The key ideas are incremental builds and local, offline queries. This article explains how the performance model works and how to make the most of it.

The first build vs. later builds

The first vg build does the full work: parsing your source and resolving relationships into the code map. After that, builds are incremental — they update only what changed rather than redoing everything:

vg build

This means the expensive work happens once, and day-to-day refreshes are quick. Treat re-running vg build like an incremental recompile.

Queries are fast and offline

Every query — vg show, vg ask, vg impact, vg path, vg tree — reads from the already-built graph artifact. Because the heavy lifting is in the build, queries are fast. And after the first use they run fully offline, so there is no network round-trip to slow them down or leak code.

Keep queries snappy

• Bound your traversals. Use --depth on vg tree to keep call trees small and fast to render.
• Prefer the precise tool. When you know the node, vg show is more focused than a broad question.
• Rebuild incrementally, not from scratch. Just run vg build again after changes; let it do the minimal update.

vg tree --depth 2
vg show

Large repositories

For big or monorepo codebases, the same model applies: one larger initial build, then fast incremental updates and offline queries. Rebuild after pulling or editing so impact and trees stay accurate without a full rebuild each time.

When things feel slow

• If a query feels heavy, narrow it — reduce depth or target a specific node.
• If results look stale, you likely need a rebuild rather than more compute.
• Confirm you are building from the repository root so the graph is complete and queries do not miss edges.

Related

See the articles on building your first code graph, keeping the graph up to date, and troubleshooting the graph.