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Notes from Data modeling with Amazon DynamoDB – Part 1 with Alex DeBrie


Check out the video here:

DynamoDB basics:

  • Table - a collection of data (similar to a table in a relational database)
  • Item - an individual record in a DynamoDB table (similar to a row in a relational database)
  • Primary Key - whenever you create a DynamoDB table you need to specify a primary key and each item in a table needs to be uniquely identified by that key
  • Attributes - additional fields on an Item (other than the primary key). You don't need to declare them in advance, in that sense DynamoDB is schemaless (as in - it's not going to enforce any pre-defined schema). Attributes can either be simple (strings, numbers etc.) or complex (lists, collections, sets).

Primary key

There are two types of primary keys:

  • Simple primary key (partition key)
  • Composite primary key (partition key + sort key)

Primary key has to uniquely identify an item so when using composite primary key it's possible (in fact - it happens very often) that there are going to be multiple items with the same partition key (but they will be uniquely identifable by combination of partition key + sort key)

DynamoDB's guiding principle: Don't allow operations that won't scale

From SQL to NoSQL

  • primary key is hugely important (almost all of your access patterns will be based off primary keys, we don't query with attributes)
  • There are no joins in DynamoDB 🙀
  • Knowing your access paterns is advance is hugely important when working with DynamoDB
  • Secondary indexes are necessary for multiple access patterns (since a single partition + sort key is not going to be enough for ensuring a large range of potential access patterns)
  • Whenever we create a secondary index data from base table is copied into secondary index with new primary key. They can be used for read-based operations (no writes)

Single table design:

All entities in one table + generic primary keys

Partition/sort keys no longer have meaningful names like "Organization" or "Author", instead we use generic PK and SK.

As we can see in the example - items that share the same partition key (but not the sort key) are going to have different attributes (because for instance - user and organization are going to have different attributes associated with them)

One-to-many relationships:

Example: an office may have multiple employees, a customer can have multiple orders etc.

Key problem: how to get information about parent item when fetching related item(s)

There are multiple strategies when it comes to handling one-to-many relationships in DynamoDB.

Denormalization + complex attribute:

Good when:

  • no access pattern on related items directly
  • limited number of related items (400kB - DynamoDB item size limit)

Denormalization + duplication

This is something you would never do in a relational database - duplicate fields from Author field to Book

Good when:

  • Duplicated data is immutable (e.g. birthday), OR
  • Duplicated data doesn't change often or is not replicated much

Composite primary key + query

Querying all items in DynamoDB with the same primary key is really fast - in essence it's a O(1) hash table lookup operation (since all those items are going to share the same partition).

All items with the same primary key are referred to as an Item collection:

With an item collection we're "pre-joining" data.

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