User Activity Database
Question
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Company Overview - HipLocal is a community application designed to facilitate communication between people in close proximity.
It is used for event planning and organizing sporting events, and for businesses to connect with their local communities.
HipLocal launched recently in a few neighborhoods in Dallas and is rapidly growing into a global phenomenon.
Its unique style of hyper-local community communication and business outreach is in demand around the world.
Executive Statement - We are the number one local community app; it's time to take our local community services global.
Our venture capital investors want to see rapid growth and the same great experience for new local and virtual communities that come online, whether their members are 10 or 10000 miles away from each other.
Solution Concept - HipLocal wants to expand their existing service, with updated functionality, in new regions to better serve their global customers.
They want to hire and train a new team to support these regions in their time zones.
They will need to ensure that the application scales smoothly and provides clear uptime data.
Existing Technical Environment - HipLocal's environment is a mix of on-premises hardware and infrastructure running in Google Cloud Platform.
The HipLocal team understands their application well, but has limited experience in global scale applications.
Their existing technical environment is as follows: " Existing APIs run on Compute Engine virtual machine instances hosted in GCP.
" State is stored in a single instance MySQL database in GCP.
" Data is exported to an on-premises Teradata/Vertica data warehouse.
" Data analytics is performed in an on-premises Hadoop environment.
" The application has no logging.
" There are basic indicators of uptime; alerts are frequently fired when the APIs are unresponsive.
Business Requirements - HipLocal's investors want to expand their footprint and support the increase in demand they are seeing.
Their requirements are: " Expand availability of the application to new regions.
" Increase the number of concurrent users that can be supported.
" Ensure a consistent experience for users when they travel to different regions.
" Obtain user activity metrics to better understand how to monetize their product.
" Ensure compliance with regulations in the new regions (for example, GDPR)
" Reduce infrastructure management time and cost.
" Adopt the Google-recommended practices for cloud computing.
Technical Requirements - " The application and backend must provide usage metrics and monitoring.
" APIs require strong authentication and authorization.
" Logging must be increased, and data should be stored in a cloud analytics platform.
" Move to serverless architecture to facilitate elastic scaling.
" Provide authorized access to internal apps in a secure manner.
Which database should HipLocal use for storing user activity?
Answers
Explanations
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Based on the technical and business requirements provided in the case study, the best option for HipLocal to store user activity would be Google Cloud's BigQuery.
BigQuery is a cloud-based fully-managed data warehouse that is optimized for handling large datasets and running complex queries quickly. It can scale elastically based on the amount of data and workload, so it can handle the increase in demand and the number of concurrent users that HipLocal requires. Additionally, BigQuery can provide usage metrics and monitoring, which is a technical requirement for HipLocal.
In terms of compliance, BigQuery is fully compliant with GDPR, which is a requirement that HipLocal must adhere to when expanding to new regions. Furthermore, logging can be increased, and data can be stored in a cloud analytics platform, which is also a technical requirement.
Cloud SQL, Cloud Spanner, and Cloud Datastore are also database options available in Google Cloud Platform, but they may not be the best fit for HipLocal's specific use case.
Cloud SQL is a fully-managed relational database service that is well-suited for applications that use traditional SQL databases like MySQL, which is what HipLocal currently uses. However, Cloud SQL may not be able to handle the scale and performance requirements of HipLocal's application when it expands globally.
Cloud Spanner is a globally-distributed relational database that provides high availability and strong consistency across regions. While it may be a good fit for HipLocal's global expansion plans, it may be more complex and costly to set up and manage compared to BigQuery.
Cloud Datastore is a NoSQL document database that can scale horizontally and store semi-structured data. However, it may not be the best fit for storing user activity data, as it is optimized for transactional data rather than analytical data, which is what HipLocal requires for better understanding how to monetize their product.
In summary, based on the technical and business requirements provided in the case study, the best database option for HipLocal to store user activity would be Google Cloud's BigQuery.
