Vectors, JSON, Bytes, Shapes and Intervals Through One REST API, on Six Databases

Intro

0:00 Vectors, JSON, bytes, shapes and intervals. Every column type of the six databases goes through the same APIs, as plain JSON : the vectors of AI models too, stored and read like any other value.

Every driver, its own way

0:15 Each database driver reads these types its own way : a vector as raw bytes, JSON as a string to parse, bytes in base64, by hand, and a point in the format of each database. With API Maker, a vector is a list of numbers, JSON is JSON, bytes are one Buffer object, and a shape goes in as GeoJSON. In this video : a table with the new types, its schema, a row saved and read back, what each database gives back, vectors on MongoDB, shapes and intervals on PostgreSQL, the same from your code, and good to know.

A table with the new types

0:54 Calm Home adds AI to its shop. On MariaDB, the marketing database gets a table of product profiles. An embedding : the vector an AI model makes of each product, to find similar ones. Real models give hundreds of numbers ; four here, to read them. Its details as JSON, the perceptual hash of its photo, eight bytes, its pick-up point, and plain notes.

Its schema

1:19 In the panel : Instance API. The instance mariadb, its database marketing, the new table, and Add Schema, made from the table. The vector is a list of numbers. JSON, the bytes and the point are strings that take objects. On MariaDB, JSON is a long text : its field gets the length of one. Save.

A row, saved and read back

1:44 API Testing. mariadb, marketing, product profiles, Save single or multiple. The row, as plain JSON : the vector as a list, the details as an object, the hash as a Buffer object, and the pick-up point as GeoJSON. Send : two hundred and one, and the row as the database keeps it. The numbers of a vector are floats of four bytes : 0.12 comes back as 0.11999999731779099. On MariaDB, JSON comes back as its text.

2:22 The bytes, as the same Buffer object, and the point, as x and y. A list sent to a text column which is not JSON is refused, the field named : nothing was saved.

Every database

2:34 Every database, the same way. Vectors : MySQL 9, MariaDB 11.7, SQL Server 2025, Oracle 23ai, and pgvector on PostgreSQL. JSON comes back as JSON on MySQL, PostgreSQL, SQL Server 2025 and Oracle 21c. Bytes are a Buffer object everywhere. And a shape is read in the form of the driver of each database.

Vectors on MongoDB

3:01 On MongoDB, a pipeline of embeddings writes BSON vectors, binary data of subtype nine, as the vector search of Atlas stores them. In API Testing, mongodb, catalog, product embeddings, Get all. Send : each vector is read as its numbers.

Shapes and intervals on PostgreSQL

3:23 On PostgreSQL, the delivery zones of the shop. Save single or multiple. A lead time as an interval object, the area as a circle, the postcodes as an array, and the rules as jsonb. Send : the interval comes back as days and hours, the circle as x, y and radius, the array as a list, and jsonb as JSON.

From your code

3:46 From your code, the same values. g.sys.db saves them in every language : in Python, and in Go, with plain lists and maps. They are read back in the same forms.

Good to know

4:00 Good to know. Bytes, intervals and the large objects of Oracle get no length in the schema. A vector of the wrong size is refused by the database : send as many numbers as the column has. Schemas made before these types keep their old fields : generate them again. And API Maker stores and reads vectors : the search by similarity is the work of your database, in a custom API.

Recap

4:27 To sum up. A vector is a list of numbers, floats of four bytes. JSON is JSON, a text on MariaDB. Bytes are a Buffer object, shapes and intervals plain objects. The same values in the generated APIs, the schema APIs and your code. Next : the schemas of your tables, and the rules they check. API Maker. Build faster, spend smarter, deliver better.