What Is Amazon DynamoDB?
Welcome to the Amazon DynamoDB Developer Guide.
Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database so that you don’t have to worry about hardware provisioning, setup, and configuration, replication, software patching, or cluster scaling.
With DynamoDB, you can create database tables that can store and retrieve any amount of data, and serve any level of request traffic. You can scale up or scale down your tables’ throughput capacity without downtime or performance degradation, and use the AWS Management Console to monitor resource utilization and performance metrics.
DynamoDB allows you to delete expired items from tables automatically to help you reduce storage usage and the cost of storing data that is no longer relevant. For more information, seeTime To Live.
DynamoDB automatically spreads the data and traffic for your tables over a sufficient number of servers to handle your throughput and storage requirements, while maintaining consistent and fast performance. All of your data is stored on solid state disks (SSDs) and automatically replicated across multiple Availability Zones in an AWS region, providing built-in high availability and data durability.
We recommend that you begin by reading the following sections:
To get started quickly with DynamoDB, see Getting Started with DynamoDB.
To learn more about application development see the following:
For best practices, how-to guides and tools, be sure to check the DynamoDB Developer Resources page: http://aws.amazon.com/dynamodb/developer-resources/.
You can use AWS Database Migration Service to migrate data from a Relational Database or MongoDB to an Amazon DynamoDB table. For more information, see AWS Database Migration Service User Guide. To learn how to use MongoDB as a migration source, see Using MongoDB as a Source for AWS Database Migration Service. To learn how to use DynamoDB as a migration target, see Using an Amazon DynamoDB Database as a Target for AWS Database Migration Service.
Amazon DynamoDB: How It Works
The following sections provide an overview of Amazon DynamoDB service components and how they interact.
After you read this introduction, try working through the Creating Tables and Loading Sample Data section, which walks you through the process of creating sample tables, uploading data, and performing some basic database operations.
For language-specific tutorials with sample code, see Getting Started with DynamoDB.
- DynamoDB Core Components
- The DynamoDB API
- Naming Rules and Data Types
- Read Consistency
- Throughput Capacity for Reads and Writes
- Partitions and Data Distribution
DynamoDB Core Components
In DynamoDB, tables, items, and attributes are the core components that you work with. A table is a collection of items, and each item is a collection of attributes. DynamoDB uses primary keys to uniquely identify each item in a table and secondary indexes to provide more querying flexibility. You can use DynamoDB Streams to capture data modification events in DynamoDB tables.
There are limits in DynamoDB. For more information, see Limits in DynamoDB.
Tables, Items, and Attributes
The following are the basic DynamoDB components:
- 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.
The following diagram shows a table named People with some example items and attributes.
Note the following about the People table:
- 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 following is another example table named Music that you could use to keep track of your music collection.
Note the following about the Music table:
- 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.
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:
- Partition key – A simple primary key, composed of one attribute known as the partition key.DynamoDB uses the partition key’s value as input to an internal hash function. The output from the hash function determines the partition (physical storage internal to DynamoDB) in which the item will be stored.
In a table that has only a partition key, no two items can have the same partition key value.
The People table described in Tables, Items, and Attributes is an example of a table with a simple primary key (PersonID). You can access any item in the People table immediately by providing the PersonId value for that item.
- Partition key and sort key – Referred to as a composite primary key, this type of key is composed of two attributes. The first attribute is the partition key, and the second attribute is the sort key.DynamoDB uses the partition key value as input to an internal hash function. The output from the hash function determines the partition (physical storage internal to DynamoDB) in which the item will be stored. All items with the same partition key are stored together, in sorted order by sort key value.
In a table that has a partition key and a sort key, it’s possible for two items to have the same partition key value. However, those two items must have different sort key values.
The Music table described in Tables, Items, and Attributes is an example of a table with a composite primary key (Artist and SongTitle). You can access any item in the Music table immediately if you provide the Artist and SongTitle values for that item.
A composite primary key gives you additional flexibility when querying data. For example, if you provide only the value for Artist, DynamoDB retrieves all of the songs by that artist. You could even provide a value for Artist and a range of SongTitle values, to retrieve only a subset of songs by a particular artist.
The partition key of an item is also known as its hash attribute. The term hash attribute derives from the use of an internal hash function in DynamoDB that evenly distributes data items across partitions, based on their partition key values.
The sort key of an item is also known as its range attribute. The term range attribute derives from the way DynamoDB stores items with the same partition key physically close together, in sorted order by the sort key value.
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.
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:
- Global secondary index – An index with a partition key and sort key that can be different from those on the table.
- Local secondary index – An index that has the same partition key as the table, but a different sort key.
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:
- Every index belongs to a table, which is called the base table for the index. In the preceding example, Music is the base table for the GenreAlbumTitle index.
- DynamoDB maintains indexes automatically. When you add, update, or delete an item in the base table, DynamoDB adds, updates, or deletes the corresponding item in any indexes that belong to that table.
- When you create an index, you specify which attributes will be copied, or projected, from the base table to the index. At a minimum, DynamoDB projects the key attributes from the base table into the index. This is the case with,
GenreAlbumTitlewhere only the key attributes from the table
Musicare projected into the 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 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:
- If a new item is added to the table, the stream captures an image of the entire item, including all of its attributes.
- If an item is updated, the stream captures the “before” and “after” image of any attributes that were modified in the item.
- If an item is deleted from the table, the stream captures an image of the entire item before it was deleted.
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 this example, the last customer, Craig Roe, will not receive an email because he doesn’t have an EmailAddress.
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.