Question: 1 / 400
How does Google Cloud Bigtable differ from traditional databases?
It uses a document-based storage model
It is designed for large analytical and operational workloads
The correct answer highlights that Google Cloud Bigtable is specifically designed to handle large analytical and operational workloads. Bigtable is a NoSQL database service that excels in managing vast amounts of data across distributed systems, making it suitable for applications that demand high throughput and low latency access to large datasets. This capability sets it apart from traditional relational databases, which often struggle with scaling to accommodate similar workloads without significant performance trade-offs.
The architecture of Bigtable allows for rapid ingestion and retrieval of data, thus enabling it to efficiently manage workloads such as time series data analysis, IoT data storage, and machine learning data preparation. Unlike many traditional databases that may prioritize transaction consistency or normalization for smaller datasets, Bigtable's design is focused on scalability and speed, which is vital for large applications.
In contrast, the other options describe aspects that do not align with Bigtable's purpose or functionality. For instance, it does not utilize a document-based storage model, as that characterizes other types of NoSQL databases such as MongoDB. The option regarding data integrity over scalability overlooks Bigtable's design, which allows for eventual consistency and prioritizes scalability for large datasets. Lastly, Bigtable is optimized for large datasets rather than small ones, which is contrary to the last option mentioned
Get further explanation with Examzify DeepDiveBetaIt focuses on data integrity over scalability
It performs best with small data sets