AWS Solutions Architect Associate

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What is Amazon DynamoDB?
DynamoDB is a fast and flexible nonrelational database service for any scale. DynamoDB enables customers to offload the administrative burdens of operating and scaling distributed databases to AWS so that they don’t have to worry about hardware provisioning, setup and configuration, throughput capacity planning, replication, software patching, or cluster scaling.
Amazon DynamoDB is a fully managed proprietary NoSQL database service that supports key-value and document data structures and is offered by Amazon.com as part of the Amazon Web Services portfolio. DynamoDB exposes a similar data model to and derives its name from Dynamo, but has a different underlying implementation. Dynamo had a multi-master design requiring the client to resolve version conflicts and DynamoDB uses synchronous replication across multiple datacenters for high durability and availability.

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Amazon DynamoDB main charateristics:
- Fully Managed
- Fast, consistent Performance
- Fine-grained access control
- Flexible









Amazon DynamoDB is a low-latency NoSQL database.
DynamoDB consists of Tables, Items, and Attributes
DynamoDb supports both document and key-value data models
DynamoDB Supported documents formats are JSON, HTML, XML
DynamoDB has 2 types of Primary Keys: Partition Key and combination of Partition Key + Sort Key (Composite Key)
DynamoDB has 2 consistency models: Strongly Consistent / Eventually Consistent
DynamoDB Access is controlled using IAM policies.
DynamoDB has fine grained access control using IAM Condition parameter dynamodb:LeadingKeys to allow users to access only the items where the partition key vakue matches their user ID.
DynamoDB Indexes enable fast queries on specific data columns
DynamoDB indexes give you a different view of your data based on alternative Partition / Sort Keys.
DynamoDB Local Secondary indexes must be created when you create your table, they have same partition Key as your table, and they have a different Sort Key.
DynamoDB Global Secondary Index an be created at any time: at table creation or after. They have a different partition Key as your table and a different sort key as your table.
A DynamoDB query operation finds items in a table using only the primary Key attribute: You provide the Primary Key name and a distinct value to search for.
A DynamoDB Scan operation examines every item in the table. By default, it return data attributes.
DynamoDB Query operation is generally more efficient than a Scan.
With DynamoDB, you can reduce the impact of a query or scan by setting a smaller page size which uses fewer read operations.
To optimize DynamoDB performance, isolate scan operations to specific tables and segregate them from your mission-critical traffic.
To optimize DynamoDB performance, try Parallel scans rather than the default sequential scan.
To optimize DynamoDB performance: Avoid using scan operations if you can: design tables in a way that you can use Query, Get, or BatchGetItems APIs.
When you scan your table in Amazon DynamoDB, you should follow the DynamoDB best practices for avoiding sudden bursts of read activity.

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What does DynamoDB manage on my behalf?
DynamoDB takes away one of the main stumbling blocks of scaling databases: the management of database software and the provisioning of the hardware needed to run it. You can deploy a nonrelational database in a matter of minutes. DynamoDB automatically scales throughput capacity to meet workload demands, and partitions and repartitions your data as your table size grows. Also, DynamoDB synchronously replicates data across three facilities in an AWS Region, giving you high availability and data durability.

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What is the consistency model of DynamoDB?
When reading data from DynamoDB, users can specify whether they want the read to be eventually consistent or strongly consistent:

- Eventually consistent reads (the default) – The eventual consistency option maximizes your read throughput. However, an eventually consistent read might not reflect the results of a recently completed write. All copies of data usually reach consistency within a second. Repeating a read after a short time should return the updated data.
- Strongly consistent reads — In addition to eventual consistency, DynamoDB also gives you the flexibility and control to request a strongly consistent read if your application, or an element of your application, requires it. A strongly consistent read returns a result that reflects all writes that received a successful response before the read.
- ACID transactions – DynamoDB transactions provide developers atomicity, consistency, isolation, and durability (ACID) across one or more tables within a single AWS account and region. You can use transactions when building applications that require coordinated inserts, deletes, or updates to multiple items as part of a single logical business operation.

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What kind of query functionality does DynamoDB support?
DynamoDB supports GET/PUT operations by using a user-defined primary key. The primary key is the only required attribute for items in a table. You specify the primary key when you create a table, and it uniquely identifies each item. DynamoDB also provides flexible querying by letting you query on nonprimary key attributes using global secondary indexes and local secondary indexes.
A primary key can be either a single-attribute partition key or a composite partition-sort key. A single-attribute partition key could be, for example, UserID. Such a single attribute partition key would allow you to quickly read and write data for an item associated with a given user ID.
DynamoDB indexes a composite partition-sort key as a partition key element and a sort key element. This multipart key maintains a hierarchy between the first and second element values. For example, a composite partition-sort key could be a combination of UserID (partition) and Timestamp (sort). Holding the partition key element constant, you can search across the sort key element to retrieve items. Such searching would allow you to use the Query API to, for example, retrieve all items for a single UserID across a range of time stamps.

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How to update and query data items with DynamoDB?
After you have created a table using the DynamoDB console or CreateTable API, you can use the PutItem or BatchWriteItem APIs to insert items. Then, you can use the GetItem, BatchGetItem, or, if composite primary keys are enabled and in use in your table, the Query API to retrieve the items you added to the table.

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Can DynamoDB be used by applications running on any operating system?
Yes. DynamoDB is a fully managed cloud service that you access via API. Applications running on any operating system (such as Linux, Windows, iOS, Android, Solaris, AIX, and HP-UX) can use DynamoDB. We recommend using the AWS SDKs to get started with DynamoDB.

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What is the maximum throughput I can provision for a single DynamoDB table?
Maximum throughput per DynamoDB table is practically unlimited. For information about the limits in place, see Limits in DynamoDB.
DynamoDB is designed to scale without limits. However, if you want to exceed throughput rates of 10,000 write capacity units or 10,000 read capacity units for an individual table, you must Contact AWS to increase it.
If you want to provision more than 20,000 write capacity units or 20,000 read capacity units from a single subscriber account, you must first contact AWS to request a limit increase.

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What is the minimum throughput I can provision for a single DynamoDB table?
The smallest provisioned throughput you can request is 1 write capacity unit and 1 read capacity unit for both auto scaling and manual throughput provisioning. Such provisioning falls within the free tier which allows for 25 units of write capacity and 25 units of read capacity. The free tier applies at the account level, not the table level. In other words, if you add up the provisioned capacity of all your tables, and if the total capacity is no more than 25 units of write capacity and 25 units of read capacity, your provisioned capacity would fall into the free tier.

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How to increase DynamoDB performance using DAX?
DAX is a DynamoDB-compatible caching service that enables you to benefit from fast in-memory performance for demanding applications.
- As an in-memory cache, DAX reduces the response times of eventually-consistent read workloads by an order of magnitude, from single-digit milliseconds to microseconds
- DAX improves response times for Eventually Consistent reads only.
- With DAX, you point your API calls to the DAX cluster instead of your table.
- If the item you are querying is on the cache, DAX will return it; otherwise, it will perform and Eventually Consistent GetItem operation to your DynamoDB table.
- DAX reduces operational and application complexity by providing a managed service that is API compatible with Amazon DynamoDB, and thus requires only minimal functional changes to use with an existing application.
- DAX is not suitable for write-intensive applications or applications that require Strongly Consistent reads.
- For read-heavy or bursty workloads, DAX provides increased throughput and potential operational cost savings by reducing the need to over-provision read capacity units. This is especially beneficial for applications that require repeated reads for individual keys.

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How to increase DynamoDB performance using ElastiCache?
- ElastiCache is an In-memory cache that sits between your application and database
- 2 different caching strategies: Lazy loading and Write Through: Lazy loading only caches the data when it is requested
- Elasticache Node failures are not fatal, just lots of cache misses
- Avoid stale data by implementing a TTL.
- Write-Through strategy writes data into cache whenever there is a change to the database. Data is never stale
- Write-Through penalty: Each write involves a write to the cache. Elasticache node failure means that data is missing until added or updated in the database.
- Elasticache is wasted resources if most of the data is never used.

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Source
AWS DYNAMODB FAQs