Case 3:17-cv-05659-WHA Document 126-17 Filed 06/28/18 Page 1 of 4
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`Exhibit 13
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`Case 3:17-cv-05659-WHA Document 126-17 Filed 06/28/18 Page 2 of 4
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`Amazon DynamoDB
`Developer Guide
`API Version 2012-08-10
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`Case 3:17-cv-05659-WHA Document 126-17 Filed 06/28/18 Page 3 of 4
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`Amazon DynamoDB Developer Guide
`SQL or NoSQL?
`
`Amazon DynamoDB, you will encounter many similarities, but also many things that are different.
`This section describes common database tasks, comparing and contrasting SQL statements with their
`equivalent DynamoDB operations.
`
`NoSQL is a term used to describe non-relational database systems that are highly available, scalable,
`and optimized for high performance. Instead of the relational model, NoSQL databases (like DynamoDB)
`use alternate models for data management, such as key-value pairs or document storage. For more
`information, see http://aws.amazon.com/nosql.
`Note
`The SQL examples in this section are compatible with the MySQL relational database
`management system.
`The DynamoDB examples in this section show the name of the DynamoDB operation, along with
`the parameters for that operation in JSON format. For code samples that use these operations,
`see Getting Started with DynamoDB (p. 53).
`
`Topics
`• SQL or NoSQL? (p. 21)
`• Accessing the Database (p. 22)
`• Creating a Table (p. 24)
`• Getting Information About a Table (p. 26)
`• Writing Data To a Table (p. 27)
`• Reading Data From a Table (p. 29)
`• Managing Indexes (p. 34)
`• Modifying Data in a Table (p. 37)
`• Deleting Data from a Table (p. 38)
`• Removing a Table (p. 39)
`
`SQL or NoSQL?
`Today's applications have more demanding requirements than ever before. For example, an online game
`might start out with just a few users and a very small amount of data. However, if the game becomes
`successful, it can easily outstrip the resources of the underlying database management system. It is not
`uncommon for web-based applications to have hundreds, thousands, or millions of concurrent users,
`with terabytes or more of new data generated per day. Databases for such applications must handle tens
`(or hundreds) of thousands of reads and writes per second.
`
`Amazon DynamoDB is well-suited for these kinds of workloads. As a developer, you can start with a small
`amount of provisioned throughput and gradually increase it as your application becomes more popular.
`DynamoDB scales seamlessly to handle very large amounts of data and very large numbers of users.
`
`The following table shows some high-level differences between a relational database management
`system (RDBMS) and DynamoDB:
`
`Characteristic
`
`Optimal Workloads
`
`Relational Database
`Management System (RDBMS)
`
`Amazon DynamoDB
`
`Ad hoc queries; data
`warehousing; OLAP (online
`analytical processing).
`
`Web-scale applications,
`including social networks,
`gaming, media sharing, and IoT
`(Internet of Things).
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`Amazon DynamoDB Developer Guide
`Accessing the Database
`
`Characteristic
`
`Data Model
`
`Data Access
`
`Performance
`
`Scaling
`
`Relational Database
`Management System (RDBMS)
`
`The relational model requires
`a well-defined schema, where
`data is normalized into tables,
`rows and columns. In addition,
`all of the relationships are
`defined among tables, columns,
`indexes, and other database
`elements.
`
`SQL (Structured Query
`Language) is the standard for
`storing and retrieving data.
`Relational databases offer a rich
`set of tools for simplifying the
`development of database-driven
`applications, but all of these
`tools use SQL.
`
`Relational databases are
`optimized for storage, so
`performance generally
`depends on the disk subsystem.
`Developers and database
`administrators must optimize
`queries, indexes, and table
`structures in order to achieve
`peak performance.
`
`It is easiest to scale up with
`faster hardware. It is also
`possible for database tables to
`span across multiple hosts in
`a distributed system, but this
`requires additional investment.
`Relational databases have
`maximum sizes for the number
`and size of files, which imposes
`upper limits on scalability.
`
`Amazon DynamoDB
`
`DynamoDB is schemaless. Every
`table must have a primary key
`to uniquely identify each data
`item, but there are no similar
`constraints on other non-key
`attributes. DynamoDB can
`manage structured or semi-
`structured data, including JSON
`documents.
`
`You can use the AWS
`Management Console or
`the AWS CLI to work with
`DynamoDB and perform ad
`hoc tasks. Applications can
`leverage the AWS software
`development kits (SDKs) to work
`with DynamoDB using object-
`based, document-centric, or low-
`level interfaces.
`
`DynamoDB is optimized for
`compute, so performance
`is mainly a function of the
`underlying hardware and
`network latency. As a managed
`service, DynamoDB insulates
`you and your applications from
`these implementation details, so
`that you can focus on designing
`and building robust, high-
`performance applications.
`
`DynamoDB is designed to scale
`out using distributed clusters
`of hardware. This design allows
`increased throughput without
`increased latency. Customers
`specify their throughput
`requirements, and DynamoDB
`allocates sufficient resources
`to meet those requirements.
`There are no upper limits on the
`number of items per table, nor
`the total size of that table.
`
`Accessing the Database
`Before your application can access a database, it must be authenticated to ensure that the application is
`allowed to use the database, and authorized so that the application can only perform actions for which it
`has permissions.
`
`The following diagram shows client interaction with a relational database, and with DynamoDB.
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