Your retail company is currently using DynamoDB to store product catalog data. Due to increasing data volumes and the need for better scalability, cost efficiency, and AI features; you have decided to

Question

Options

• AExport the DynamoDB data to CSV files, upload them to Cloud Storage, and use the cbt CLI to
• BCreate a Dataflow pipeline using the DynamoDBIO and BigtableIO connectors to stream data from
• CDevelop a custom script using the DynamoDB and Bigtable APIs to directly transfer data between
• DUse Dataproc to export the data from DynamoDB and load it into Bigtable.

• A
  4% (1)
• B
  77% (20)
• C
  4% (1)
• D
  15% (4)

Explanation

Dataflow is the optimal choice for migrating from DynamoDB to Bigtable with minimal downtime, minimal effort, and data consistency. Dataflow is a fully managed, serverless stream and batch processing service. It provides pre-built connectors (DynamoDBIO and BigtableIO) that handle the complexities of reading from DynamoDB and writing to Bigtable without custom code. It supports streaming mode, which enables near-real-time data transfer and minimizes downtime. It also scales automatically, handles retries and fault tolerance, and is cost-effective since you only pay for what you use. Option A (CSV export) requires multiple manual steps and risks data inconsistency. Option C (custom script) requires significant development effort. Option D (Dataproc) is designed for Spark/Hadoop workloads and is overkill for a direct database migration.

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