Which of the following are use cases for Amazon DynamoDB? Choose 3 answers
A.
Storing BLOB data.
B.
Managing web sessions.
C.
Storing JSON documents.
D.
Storing metadata for Amazon S3 objects.
E.
Running relational joins and complex updates.
F.
Storing large amounts of infrequently accessed data.
BCD
B, C and D is the right answer
It should be BCF the dynamodb is not fit for joins
CEF
thanks for ur excluded answers
BCD
BCD are correct options, AEF are not applicable to Dyanmodb at all.
BCD is the answer
Ideal Usage Patterns
•Amazon DynamoDB is ideal for existing or new applications that need a flexible NoSQL database with low read and write latencies, and the ability to scale storage and throughput up or down as needed without code changes or downtime.
•Use cases require a highly available and scalable database because downtime or performance degradation has an immediate negative impact on an organization’s business. for e.g. mobile apps, gaming, digital ad serving, live voting and audience interaction for live events, sensor networks, log ingestion, access control for web-based content, metadata storage for Amazon S3 objects, e-commerce shopping carts, and web session management
Managing web sessions
Storing JSON documents
Storing metadata for Amazon S3 objects
Can store blobs up to 400k, but B,C and D are correct too.
E and F are distractors, not sure why someone suggested them
BCD
BCD
BCD
ABC
Sorry, correct answers are B,C,D.
Blobs are large files, should be stored on S3.
BCD is the ans. D_Trump, did you ask Hillary ?
Its B, C, & D.
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.
A,B,C are answer true.
BCD
BCD
Q: When should I use Amazon DynamoDB vs Amazon S3?
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
Answer BCD
https://aws.amazon.com/dynamodb/faqs/
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.
Q: Can I use the AWS Management Console to view and edit JSON documents?
Yes. The AWS Management Console provides a simple UI for exploring and editing the data stored in your DynamoDB tables, including JSON documents
http://docs.aws.amazon.com/amazondynamodb/latest/developerguide/GuidelinesForItems.html
DynamoDB currently limits the size of the items that you store in tables. For more information, see Limits in DynamoDB. Your application, however, might need to store more data in an item than the DynamoDB size limits permit. To work around this issue, you can store the large attributes as an object in Amazon Simple Storage Service (Amazon S3), and store the object identifier in your item. You can also use the object metadata support in Amazon S3 to store the primary key value of the corresponding item as Amazon S3 object metadata. This use of metadata can help with future maintenance of your Amazon S3 objects.
BCD is correct
BCD
When should I use Amazon DynamoDB vs Amazon S3?
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.
What is a document store?
A document store provides support for storing, querying and updating items in a document format such as JSON, XML, and HTML.
Above statements from AWS justifies BCD as correct answer