Suggest an editImprove this articleRefine the answer for “What does the term "scaling" mean in the context of MongoDB?”. Your changes go to moderation before they’re published.Approval requiredContentWhat you’re changing🇺🇸EN🇺🇦UAPreviewTitle (EN)Short answer (EN)Scaling is increasing a system's computing resources so it can handle more data and requests without a drop in performance: either vertically (strengthening a single machine) or horizontally (adding new servers through sharding and replication). **Key point:** MongoDB was designed from the start to be easy to scale horizontally, unlike many SQL DBMSs.Shown above the full answer for quick recall.Answer (EN)ImageScaling in the context of MongoDB is **increasing a system's computing resources so it can handle more data and requests without a drop in performance**. In MongoDB the term covers two approaches: ### 1. Vertical scaling (scale-up) Increasing the power of **a single machine**: - more CPU - more RAM - faster disks The upside: simple. The downside: there's a limit, you can't keep "beefing up the hardware" forever. ### 2. Horizontal scaling (scale-out) Adding **new servers to the cluster** and distributing data/load across them: - sharding, data is split across several nodes - replication, read load is spread across secondary nodes The upside: it can scale almost indefinitely. The downside: the infrastructure is more complex. ### The key idea MongoDB was built from the start to be **easy to scale horizontally**, unlike many SQL DBMSs. ### Summary Scaling in MongoDB is a set of ways to expand the system so it can handle larger volumes of data and requests. That can mean either strengthening a single server, or spreading the load across many machines.For the reviewerNote to the moderator (optional)Visible only to the moderator. Helps review go faster.