Save, Update and Remove on Any Database with the Same API Calls

Intro

0:00 Save one row or many, update and remove by a filter, push into an array : the same calls on every engine. In this video, the coupons of a festival, and a wishlist.

Writing data, the usual way

0:12 Writing data usually means an insert endpoint per table, and a loop for many rows, half a batch written when one row is wrong, and an array read and written back whole to add one item. With API Maker, one save for one row or many, the whole batch checked before a row is written, and push and pull in place, on MongoDB. In this video : several rows saved at once, one bad row, update many, remove by query, and push and pull.

Several rows at once

0:42 API Testing, mariadb, marketing, coupons, Save single-multiple. Two coupons for the Festival of Lights, in one array. The second has a discount of twenty, in words. Four hundred : the field and the reason. And neither coupon is saved : the whole array is checked first. Twenty, as a number. Two hundred and one : both coupons, numbered by the database.

Many rows at once

1:12 Update many. A find, the two codes, and the data to set : a thousand uses each. updatedRowsCount, two. One call, every row the find matches. Remove by query, the same find. deletedRowsCount, two, and the rows as they were, with their ids : enough to log what went, or to put it back.

Arrays of MongoDB

1:37 On MongoDB, the wishlists : a wishlist of a customer, Festival gifts, with the Ash nightstand. Saved. Array operations. The body names the document and what to do with it. The find picks the wishlist by its name. In operations, push, on the path items, with dataToPush : the Glow strip. Two items now. Pull takes a queryToRemove instead : the product id of the nightstand. One left. The document is changed in place, never read and written back whole.

Good to know

2:14 Update by id changes one row, and replace by id a whole document of MongoDB. Master save writes rows of several tables, across databases, in one call : video nine. Every write of a SCHEMA API goes through the schema : conversions, rules and encryption, videos three and four. And a write drops the cached answers of its table : video twenty nine.

Built on standards

2:38 One shape of write on every engine. A batch checked before a single row is written. So a client, or an AI assistant, never leaves half a batch behind.

Recap

2:50 To sum up. One save for one row or many. One bad row, nothing written. Update many and remove by query. Push and pull in place. Next : master save, a tree of rows across databases in one call. API Maker. Build faster, spend smarter, deliver better.