Case 3:17-cv-05659-WHA Document 126-20 Filed 06/28/18 Page 1 of 5
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`Exhibit 16
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`Case 3:17-cv-05659-WHA Document 126-20 Filed 06/28/18 Page 2 of 5
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`Frequently Asked Quesions About
`Amazon DynamoDB
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`Case 3:17-cv-05659-WHA Document 126-20 Filed 06/28/18 Page 3 of 5
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`You can construct a free-form conditional expression that combines multiple
`conditional clauses, including nested clauses. Conditional operations allow users to
`implement optimistic concurrency control systems on DynamoDB. For more
`information on conditional operations, please see our documentation.
`
`Q: Are expressions supported for key conditions?
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`Yes, you can specify an expression as part of the Query API call to filter results based
`on values of primary keys on a table using the KeyConditionExpression parameter.
`
`Q: Are expressions supported for partition and partition-sort keys?
`
`Yes, you can use expressions for both partition and partition-sort keys. Refer to the
`documentation page for more information on which expressions work on partition and
`partition-sort keys.
`
`Q: Does Amazon DynamoDB support increment or decrement operations?
`
`Yes, Amazon DynamoDB allows atomic increment and decrement operations on
`scalar values.
`
`Q: When should I use Amazon DynamoDB vs a relational database engine on
`Amazon RDS or Amazon EC2?
`
`Today’s web-based applications generate and consume massive amounts of data. For
`example, an online game might start out with only a few thousand users and a light
`database workload consisting of 10 writes per second and 50 reads per second.
`However, if the game becomes successful, it may rapidly grow to millions of users and
`generate tens (or even hundreds) of thousands of writes and reads per second. It may
`also create terabytes or more of data per day. Developing your applications against
`Amazon DynamoDB enables you to start small and simply dial-up your request
`capacity for a table as your requirements scale, without incurring downtime. You pay
`highly cost-efficient rates for the request capacity you provision, and let Amazon
`DynamoDB do the work over partitioning your data and traffic over sufficient server
`capacity to meet your needs. Amazon DynamoDB does the database management
`and administration, and you simply store and request your data. Automatic replication
`and failover provides built-in fault tolerance, high availability, and data durability.
`Amazon DynamoDB gives you the peace of mind that your database is fully managed
`and can grow with your application requirements.
`
`While Amazon DynamoDB tackles the core problems of database scalability,
`management, performance, and reliability, the datamodel, just like any NoSQL, must
`be designed specifically for the access patterns required by the application. In other
`words, running adhoc queries on DynamoDB can be inefficient. Refer to the design
`guidance that shows how to effectively migrate from any Relational database to
`DynamoDB. If your workload requires this functionality, or you are looking for
`compatibility with an existing relational engine, you may wish to run a relational engine
`on Amazon RDS or Amazon EC2. While relational database engines provide robust
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`Case 3:17-cv-05659-WHA Document 126-20 Filed 06/28/18 Page 4 of 5
`features and functionality, scaling a workload beyond a single relational database
`instance is highly complex and requires significant time and expertise. As such, if you
`anticipate scaling requirements for your new application and do not need relational
`features, Amazon DynamoDB may be the best choice for you.
`
`Q: How does Amazon DynamoDB differ from Amazon SimpleDB?
`
`Which should I use? Both services are non-relational databases that remove the work
`of database administration. Amazon DynamoDB focuses on providing seamless
`scalability and fast, predictable performance. It runs on solid state disks (SSDs) for
`low-latency response times, and there are no limits on the request capacity or storage
`size for a given table. This is because Amazon DynamoDB automatically partitions
`your data and workload over a sufficient number of servers to meet the scale
`requirements you provide. In contrast, a table in Amazon SimpleDB has a strict
`storage limitation of 10 GB and is limited in the request capacity it can achieve
`(typically under 25 writes/second); it is up to you to manage the partitioning and re-
`partitioning of your data over additional SimpleDB tables if you need additional scale.
`While SimpleDB has scaling limitations, it may be a good fit for smaller workloads that
`require query flexibility. Amazon SimpleDB automatically indexes all item attributes
`and thus supports query flexibility at the cost of performance and scale.
`
`Amazon CTO Werner Vogels' DynamoDB blog post provides additional context on the
`evolution of non-relational database technology at Amazon.
`
`Q: When should I use Amazon DynamoDB vs Amazon S3?
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`Amazon DynamoDB stores structured data, indexed by primary key, and allows low
`latency read and write access to items ranging from 1 byte up to 400KB. Amazon S3
`stores unstructured blobs and suited for storing large objects up to 5 TB. In order to
`optimize your costs across AWS services, large objects or infrequently accessed data
`sets should be stored in Amazon S3, while smaller data elements or file pointers
`(possibly to Amazon S3 objects) are best saved in Amazon DynamoDB.
`
`Q: Can DynamoDB be used by applications running on any operating system?
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`Yes. DynamoDB is a fully managed cloud service that you access via API. DynamoDB
`can be used by applications running on any operating system (e.g. Linux, Windows,
`iOS, Android, Solaris, AIX, HP-UX, etc.). We recommend using the AWS SDKs to get
`started with DynamoDB. You can find a list of the AWS SDKs on our Developer
`Resources page. If you have trouble installing or using one of our SDKs, please let us
`know by posting to the relevant AWS Forum.
`
`Data models and APIs
`
`Q: What is the Data Model?
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`Case 3:17-cv-05659-WHA Document 126-20 Filed 06/28/18 Page 5 of 5
`The data model for Amazon DynamoDB is as follows:
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`Table: A table is a collection of data items – just like a table in a relational database is
`a collection of rows. Each table can have an infinite number of data items. Amazon
`DynamoDB is schema-less, in that the data items in a table need not have the same
`attributes or even the same number of attributes. Each table must have a primary key.
`The primary key can be a single attribute key or a “composite” attribute key that
`combines two attributes. The attribute(s) you designate as a primary key must exist for
`every item as primary keys uniquely identify each item within the table.
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`Item: An Item is composed of a primary or composite key and a flexible number of
`attributes. There is no explicit limitation on the number of attributes associated with an
`individual item, but the aggregate size of an item, including all the attribute names and
`attribute values, cannot exceed 400KB.
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`Attribute: Each attribute associated with a data item is composed of an attribute name
`(e.g. “Color”) and a value or set of values (e.g. “Red” or “Red, Yellow, Green”).
`Individual attributes have no explicit size limit, but the total value of an item (including
`all attribute names and values) cannot exceed 400KB.
`
`Q: Is there a limit on the size of an item?
`
`The total size of an item, including attribute names and attribute values, cannot
`exceed 400KB. Refer to the design guidance for using ‘Composite Sort Keys’ to
`design for items that exceed the 400K limit.
`
`Q: Is there a limit on the number of attributes an item can have?
`
`There is no limit to the number of attributes that an item can have. However, the total
`size of an item, including attribute names and attribute values, cannot exceed 400KB.
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`Q: What are the APIs?
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`CreateTable – Creates a table and specifies the primary index used for data
`access.
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`UpdateTable – Updates the provisioned throughput values for the given table.
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`DeleteTable – Deletes a table.
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`DescribeTable – Returns table size, status, and index information.
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`ListTables – Returns a list of all tables associated with the current account and
`endpoint.
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`PutItem – Creates a new item, or replaces an old item with a new item (including all
`the attributes). If an item already exists in the specified table with the same primary
`key, the new item completely replaces the existing item. You can also use
`conditional operators to replace an item only if its attribute values match certain
`conditions, or to insert a new item only if that item doesn’t already exist.
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