KindleYou is a location-based social search mobile app that allows users to like or dislike other users, and allows users to chat if both parties liked each other in the app.
It has more than 1 billion customers across the world.
They use DynamoDB to support the mobile application and S3 to host the images and other documents shared between users.
KindleYou is planning to understand the relationships between customers and store billions of relationships and querying the graph with milliseconds latency thereby efficiently navigate between highly connected datasets to evaluate use cases such as recommendation engines, knowledge graphs, etc.
which AWS Service provides you the support.
Select 1 option.
Click on the arrows to vote for the correct answer
A. B. C. D.Answer : B.
Option A is incorrect - Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.
DynamoDB lets you offload the administrative burdens of operating and scaling a distributed database, so that you don't have to worry about hardware provisioning, setup and configuration, replication, software patching, or cluster scaling.
https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/Introduction.htmlOption B is correct -Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets.
The core of Neptune is a purpose-built, high-performance graph database engine that is optimized for storing billions of relationships and querying the graph with milliseconds latency.
https://docs.aws.amazon.com/neptune/latest/userguide/intro.htmlOption C is incorrect -
C.
No.Amazon EMR is a managed cluster platform that simplifies running big data frameworks, such as Apache Hadoop and Apache Spark, on AWS to process and analyze vast amounts of data.
By using these frameworks and related open-source projects, such as Apache Hive and Apache Pig, you can process data for analytics purposes and business intelligence workloads.
Additionally, you can use Amazon EMR to transform and move large amounts of data into and out of other AWS data stores and databases, such as Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB.https://docs.aws.amazon.com/emr/latest/ManagementGuide/emr-what-is-emr.html.
Option D is incorrect -
The Amazon Redshift service manages all of the work of setting up, operating, and scaling a data warehouse.
These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.
https://docs.aws.amazon.com/redshift/latest/mgmt/overview.htmlBased on the scenario provided, KindleYou is looking for a solution to manage and query relationships between billions of customers efficiently. This requires a database that can handle highly connected datasets and provide low-latency access for graph queries.
Among the options provided, the best choice for this scenario would be Amazon Neptune, which is a fully-managed graph database service built for highly connected datasets. It is designed to store and query graph data with low latency and high availability, making it ideal for use cases such as recommendation engines, fraud detection, and knowledge graphs.
Amazon Neptune supports various graph models and can store billions of relationships with ease. It uses a highly available and durable storage backend, allowing you to scale your graph databases as needed. Additionally, Neptune provides easy integration with other AWS services such as S3, Lambda, and CloudWatch for data ingestion and processing.
DynamoDB, on the other hand, is a NoSQL database that can handle large datasets, but it may not be as efficient for highly connected datasets and graph queries as Neptune. Amazon EMR and Amazon Redshift are also not suitable for managing relationships and querying graph data efficiently.
In conclusion, the best option for KindleYou to efficiently manage and query relationships between billions of customers with low latency would be Amazon Neptune.