Best Database Offering for Self-Driving Car Project
Question
You are managing a project for a start-up that is working on developing a product to be used for self-driving cars. The edge devices will collect the data on the cars, and analysis on the ingested real-time data needs to be performed at high speed.
The performed analysis will track driver behavior. Which of the below database offering from Google Cloud would you prefer to use in this solution?
Answers
Explanations
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: A.
Option A is Correct.
As this scenario requires us to use a database that can handle high workloads and perform analytics at a fast pace, Cloud Bigtable would be an appropriate choice.
Option B is Incorrect.
Firestore is a serverless document database, and hence it will not serve the purpose as required in this scenario.
Option C is Incorrect.
Distributed SQL database, cloud spanner will not be a correct choice for this solution, as the scenario requires performing high-speed analytics.
Option D is Incorrect.
Datastream is not the right choice for this solution because data stream helps in performing replication and synchronization of data across various systems, including databases, storage systems, etc.
https://cloud.google.com/bigtable https://cloud.google.com/firestore https://cloud.google.com/spanner https://cloud.google.com/datastreamFor the given scenario, where the start-up is developing a product for self-driving cars, the edge devices will collect real-time data, and high-speed analysis will be performed on this data. The analysis will track driver behavior. Based on these requirements, the most suitable database offering from Google Cloud would be Cloud Spanner.
Cloud Spanner is a fully managed, horizontally scalable, relational database service that provides strong consistency and high availability. It offers automatic sharding and synchronous replication for high performance and fault tolerance. With Cloud Spanner, data can be distributed across multiple regions and zones, ensuring low-latency access to data from anywhere in the world.
The key advantages of using Cloud Spanner in this scenario are:
High speed: Cloud Spanner is designed for high performance and can handle real-time data analysis at high speed. It offers low latency for both reads and writes, making it an ideal choice for real-time applications.
Scalability: Cloud Spanner is horizontally scalable and can handle large amounts of data without any degradation in performance. It can also scale up or down automatically based on the workload, making it a flexible and cost-effective solution.
Strong consistency: Cloud Spanner provides strong consistency across all nodes in the database, ensuring that all clients see the same data at the same time. This is critical for applications that require accurate and up-to-date data.
Relational database: Cloud Spanner is a relational database, which means that it offers a familiar SQL interface and can work with existing SQL tools and libraries. This makes it easy to integrate with other systems and applications.
In contrast, Cloud Bigtable is a NoSQL database designed for handling large amounts of unstructured data, while Firestore is a document database designed for mobile and web applications. Datastream is a service for real-time data replication, but it does not provide a database for analysis.
Therefore, based on the given requirements, Cloud Spanner would be the most suitable database offering from Google Cloud for this solution.
