PROFESSIONAL-DATA-ENGINEER Question #53: Real Exam Question with Answer & Explanation

Question

You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required. You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)

Options

• ARedis is a key-value store (and in many cases used as in-memory and non persistent cache). It is not designed for "100TB per year" of highly available storage.
• BHBase is similar to Google Bigtable, fits the requirements perfectly: highly available, scalable and with very low latency.
• CMySQL is a relational DB, designed precisely for ACID transactions and not for the stated requirements. Also, growth may be an issue.
• DMongoDB is a document-db used for high volume data and maintains currently used data in RAM, so performance is usually really good. Should also fit the
• ECassandra is designed precisely for highly available massive datasets, and a fine tuned cluster may offer low latency in reads. Fits the requirements.
• FHDFS with Hive is great for OLAP and data-warehouse scenarios, allowing to solve map-reduce problems using an SQL subset, but the latency is usually really

Explanation

Explanation/Reference: requirements well. high (we may talk about seconds, not milliseconds, when obtaining results), so this does not complies with the requirements.

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