Google BigQuery vs Google Cloud Bigtable: What are the differences?
Google BigQuery: Analyze terabytes of data in seconds. Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.; Google Cloud Bigtable: The same database that powers Google Search, Gmail and Analytics. Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.
Google BigQuery belongs to "Big Data as a Service" category of the tech stack, while Google Cloud Bigtable can be primarily classified under "NoSQL Database as a Service".
Some of the features offered by Google BigQuery are:
- All behind the scenes- Your queries can execute asynchronously in the background, and can be polled for status.
- Import data with ease- Bulk load your data using Google Cloud Storage or stream it in bursts of up to 1,000 rows per second.
- Affordable big data- The first Terabyte of data processed each month is free.
On the other hand, Google Cloud Bigtable provides the following key features:
- Unmatched Performance: Single-digit millisecond latency and over 2X the performance per dollar of unmanaged NoSQL alternatives.
- Open Source Interface: Because Cloud Bigtable is accessed through the HBase API, it is natively integrated with much of the existing big data and Hadoop ecosystem and supports Google’s big data products. Additionally, data can be imported from or exported to existing HBase clusters through simple bulk ingestion tools using industry-standard formats.
- Low Cost: By providing a fully managed service and exceptional efficiency, Cloud Bigtable’s total cost of ownership is less than half the cost of its direct competition.
"High Performance" is the top reason why over 17 developers like Google BigQuery, while over 5 developers mention "High performance" as the leading cause for choosing Google Cloud Bigtable.
Sentry, Vine Labs, and Webedia are some of the popular companies that use Google BigQuery, whereas Google Cloud Bigtable is used by Spotify, Resultados Digitais, and Rainist. Google BigQuery has a broader approval, being mentioned in 156 company stacks & 39 developers stacks; compared to Google Cloud Bigtable, which is listed in 17 company stacks and 3 developer stacks.
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