For 50 TB of frequently updated, streaming financial time-series data and migrating existing Hadoop jobs to the cloud, which storage product is most appropriate?
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Correct answer: Cloud Bigtable.
Why this is the answer
Cloud Bigtable is ideal for this scenario because it's a high-throughput, low-latency NoSQL wide-column database specifically designed for large analytical and operational workloads, including time-series data and streaming applications. Its compatibility with HBase APIs makes it suitable for migrating existing Hadoop jobs. Google BigQuery is an analytical data warehouse, excellent for large-scale ad-hoc queries but not optimized for frequent, low-latency updates on individual rows. Google Cloud Storage is object storage, best for unstructured data and archives, not for transactional or frequently updated structured data. Google Cloud Datastore (now Firestore in Datastore mode) is a NoSQL document database, better for smaller datasets and web/mobile applications, and not designed for the scale and throughput of 50 TB of streaming time-series data.
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