DynamoDB Notes

 

       Amazon DynamoDB is a fast and flexible NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale. Its flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad-tech, IoT, and many other applications.

 

       DynamoDB provides on-demand backup capability.

 

       You can create on-demand backups and enable point-in-time recovery for your Amazon DynamoDB tables.

 

       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. 

 

       DynamoDB synchronously replicates data across three facilities in an AWS Region, giving you high availability and data durability.

 

       Consistency Models:

       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.

 

Query Functionality

 

       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.

 

       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. 

 

       Maximum throughput per DynamoDB table is practically unlimited

 

       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.

 

       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 string, number, or binary. There are no such restrictions for other, non-key attributes.

 

       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:

 

       A new item is added to the table: The stream captures an image of the entire item, including all of its attributes.

       An item is updated: The stream captures the "before" and "after" image of any attributes that were modified in the item.

       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.

 

       Amazon DynamoDB is available in multiple AWS Regions around the world. Each Region is independent and isolated from other AWS Regions. For example, if you have a table called People in the us-east-2 Region and another table named People in the us-west-2 Region, these are considered two entirely separate tables. 

 

       When your application writes data to a DynamoDB table and receives an HTTP 200 response (OK), the write has occurred and is durable. The data is eventually consistent across all storage locations, usually within one second or less.

 

Eventually Consistent Reads

       When you read data from a DynamoDB table, the response might not reflect the results of a recently completed write operation. The response might include some stale data. If you repeat your read request after a short time, the response should return the latest data.

       DynamoDB uses eventually consistent reads, unless you specify otherwise. Read operations (such as GetItemQuery, and Scan) provide a ConsistentRead parameter. If you set this parameter to true, DynamoDB uses strongly consistent reads during the operation.

Strongly Consistent Reads

       When you request a strongly consistent read, DynamoDB returns a response with the most up-to-date data, reflecting the updates from all prior write operations that were successful. However, this consistency comes with some disadvantages:

       A strongly consistent read might not be available if there is a network delay or outage. In this case, DynamoDB may return a server error (HTTP 500).

       Strongly consistent reads may have higher latency than eventually consistent reads.

       Strongly consistent reads are not supported on global secondary indexes.

       Strongly consistent reads use more throughput capacity than eventually consistent reads. For details, see Read/Write Capacity Mode