Each logical container (a Pod) has a set of data objects called Didgets (short for Data Widgets) where each one is assigned a unique 64-bit number as its ID. Ea

Each logical container (a Pod) has a set of data objects called Didgets (short for Data Widgets) where each one is assigned a unique 64-bit number as its ID. Each tag is defined with a data type (e.g. Person.FirstName has type STRING) using a schema like how a column in a relational table is defined. All tags within the same context are stored together in a highly optimized Key-Value store (also stored within specialized Didgets) like how a columnar store database stores all the data for a single column separately. So if you attach a tag like Person.FirstName = 'John' to a photo of John that is stored in a Didgets with ID = 123; then within the tag the value of 'John' is mapped to the key 123 within the Person.FirstName tag store. This makes it extremely efficient to find all the Didgets where 'John' was attached as a person's first name. It can also find everything where the first name starts with 'J' or a vowel (using regex). The values within each tag store are de-duplicated and reference counted. In the example, the value 'John' is stored once. If 100 things have 'John' attached, then its reference count is 100. This makes it extremely fast to find everything with the 10 most popular names. The tags were so efficient and fast that I built relational tables using them that are often faster to query than traditional database systems. In this case the 'Key' each value is mapped to is the rowID within the table. Here is a video showing how that compares to SQLite: https://www.youtube.com/watch?v=Va5ZqfwQXWI https://www.youtube.com/watch?v=Va5ZqfwQXWI