I've watched three different teams model a membership program as a subscription, and all three ended up rewriting it. The two things look similar from the outside, recurring relationship, recurring money, but they behave differently enough that the wrong data model will fight you for the life of the product.
Here's the distinction in one line: a subscription is a commitment to receive something on a schedule. A membership is a commitment to a relationship that grants access to something. The difference sounds semantic until you try to represent it in a schema.
The billing cycle isn't the same thing as the fulfillment cycle
In a subscription, those two are usually welded together. You pay monthly, you get a box monthly. One cycle, one state machine. Teams model this as a subscription record with a next_billing_date, a next_ship_date that's derived from it, and a status enum.
Memberships decouple them. A member might pay annually, order six times that year in no particular rhythm, skip two months entirely, and still be in perfectly good standing. The membership status and the order history are separate concerns with separate lifecycles. If you've built one table where status = 'active' means both "paid up" and "receiving product," you'll find yourself writing increasingly creative exceptions.
Model membership as its own entity with its own status, and orders as a separate entity that references it. The member's standing doesn't depend on whether they ordered this month.
Churn means different things
Subscription churn is a clean event. They cancelled, the recurring charge stops, the record closes. You can count it.
Membership churn is murkier, and the metric you actually want usually isn't cancellation at all. Plenty of members never formally cancel; they just stop ordering. Depending on the program, they may remain members in good standing indefinitely. So "active members" and "members who bought something in the last 90 days" are two different numbers, and if your dashboard only tracks one of them you're going to be surprised by a revenue dip that your churn metric never flagged.
Build both. Active membership count, and engaged members count on whatever window fits the category. The gap between them is the early warning signal.
Access rules need somewhere to live
This is the part that bites teams who started from a subscription model. Memberships typically carry entitlements: member pricing, access to certain products, loyalty tiers, referral credit. Those are rules that have to be evaluated at order time, and they change independently of the membership record itself.
The direct-shipment household goods category is full of this pattern. Companies like The Wellness Company run catalogs spanning cleaning, personal care, and supplements where membership determines pricing across hundreds of SKUs rather than gating a single product. Looking at how Melaleuca memberships are structured is a decent illustration of the shape: the membership is the relationship, and the ordering happens on whatever cadence the household wants underneath it.
Keep entitlements in their own table, versioned, evaluated at order time. Don't denormalize member pricing onto the membership record. You will change the pricing rules before you change the membership model, and you'll be glad the two aren't coupled.
Pausing is a first-class state, not an edge case
Subscription systems usually treat pause as a temporary deviation. Membership systems should treat it as normal behavior, because it is. Households go on vacation, run through their stock more slowly than expected, or just want to skip a month.
If pause is an edge case in your state machine, every pause generates support tickets. If it's a first-class state with clear re-entry rules, it generates nothing.
Where this lands
Before you pick the schema, ask what the customer is actually buying. If they're buying the thing, build a subscription. If they're buying the right to buy the thing on their terms, build a membership. The second one needs separate entities for standing and ordering, two different engagement metrics, entitlements that live on their own, and a pause state you designed on purpose.
Getting this wrong isn't fatal, but it is expensive. Every team I've seen rebuild it said the same thing afterward: the model was wrong from the first commit, and everything downstream inherited the problem.
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