• Tables – Similar to other database systems, DynamoDB stores data in tables. A table is a collection of data. For example, see the example table called People that you could use to store personal contact information about friends, family, or anyone else of interest. You could also have a Cars table to store information about vehicles that people drive.
• Items – Each table contains multiple items. An item is a group of attributes that are uniquely identifiable among all of the other items. In a People table, each item represents a person. For a Cars table, each item represents one vehicle. Items in DynamoDB are similar in many ways to rows, records, or tuples in other database systems. In DynamoDB, there is no limit to the number of items you can store in a table.
• Attributes – Each item is composed of one or more attributes. An attribute is a fundamental data element, something that does not need to be broken down any further. For example, an item in a People table contains attributes called PersonID, LastName, FirstName, and so on. For a Department table, an item might have attributes such as DepartmentID, Name, Manager, and so on. Attributes in DynamoDB are similar in many ways to fields or columns in other database systems.

• Each item in the table has a unique identifier, or primary key, that distinguishes the item from all of the others in the table. In the People table, the primary key consists of one attribute (PersonID).
• Other than the primary key, the People table is schemaless, which means that neither the attributes nor their data types need to be defined beforehand. Each item can have its own distinct attributes.
• Most of the attributes are scalar, which means that they can have only one value. Strings and numbers are common examples of scalars.
• Some of the items have a nested attribute (Address). DynamoDB supports nested attributes up to 32 levels deep.

• The primary key for Music consists of two attributes (Artist and SongTitle). Each item in the table must have these two attributes. The combination of Artist and SongTitledistinguishes each item in the table from all of the others.
• Other than the primary key, the Music table is schemaless, which means that neither the attributes nor their data types need to be defined beforehand. Each item can have its own distinct attributes.
• One of the items has a nested attribute (PromotionInfo), which contains other nested attributes. DynamoDB supports nested attributes up to 32 levels deep.

Primary Key

When you create a table, in addition to the table name, you must specify the primary key of the table. The primary key uniquely identifies each item in the table, so that no two items can have the same key.

DynamoDB supports two different kinds of primary keys:

Each primary key attribute must be a scalar (meaning that it can hold only a single value). The only data types allowed for primary key attributes are a string, number, or binary. There are no such restrictions for other, non-key attributes.

Secondary Indexes

You can create one or more secondary indexes on a table. A secondary index lets you query the data in the table using an alternate key, in addition to queries against the primary key. DynamoDB doesn’t require that you use indexes, but they give your applications more flexibility when querying your data. After you create a secondary index on a table, you can read data from the index in much the same way as you do from the table.

DynamoDB supports two kinds of indexes:

You can define up to 5 global secondary indexes and 5 local secondary indexes per table.

In the example Music table shown previously, you can query data items by Artist (partition key) or by Artist and SongTitle (partition key and sort key). What if you also wanted to query the data by Genre and AlbumTitle? To do this, you could create an index on Genre and AlbumTitle, and then query the index in much the same way as you’d query the Music table.

The following diagram shows the example Music table, with a new index called GenreAlbumTitle. In the index, Genre is the partition key and AlbumTitle is the sort key.

Note the following about the GenreAlbumTitle index:

You can query the GenreAlbumTitle index to find all albums of a particular genre (for example, all Rock albums). You can also query the index to find all albums within a particular genre that have certain album titles (for example, all Country albums with titles that start with the letter H).

DynamoDB Streams

DynamoDB Streams is an optional feature that captures data modification events in DynamoDB tables. The data about these events appear in the stream in near real time, and in the order that the events occurred.

Each event is represented by a stream record. If you enable a stream on a table, DynamoDB Streams writes a stream record whenever one of the following events occurs:

Each stream record also contains the name of the table, the event timestamp, and other metadata. Stream records have a lifetime of 24 hours; after that, they are automatically removed from the stream.

You can use DynamoDB Streams together with AWS Lambda to create a trigger—code that executes automatically whenever an event of interest appears in a stream. For example, consider a Customers table that contains customer information for a company. Suppose that you want to send a “welcome” email to each new customer. You could enable a stream on that table, and then associate the stream with a Lambda function. The Lambda function would execute whenever a new stream record appears, but only process new items added to the Customers table. For any item that has an EmailAddress attribute, the Lambda function would invoke Amazon Simple Email Service (Amazon SES) to send an email to that address.

In addition to triggers, DynamoDB Streams enables powerful solutions such as data replication within and across AWS regions, materialized views of data in DynamoDB tables, data analysis using Kinesis materialized views, and much more.