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Google BigQuery vs DATOS: 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.; DATOS: Acquiring and management of the clickstream data. It is focused on acquiring and management of the clickstream data We know everything about clickstream data - we can build custom panels, we can predict users’ behavior or we can deliver just raw data.
Our goal - to be flexible and useful for our customers..
Google BigQuery and DATOS can be primarily classified as "Big Data as a Service" tools.
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, DATOS provides the following key features:
- Clickstream Data
- Web-traffic Data
- Web Scraping Data
Pros of DATOS
Pros of Google BigQuery
- High Performance28
- Easy to use25
- Fully managed service22
- Cheap Pricing19
- Process hundreds of GB in seconds16
- Big Data12
- Full table scans in seconds, no indexes needed11
- Always on, no per-hour costs8
- Good combination with fluentd6
- Machine learning4
- Easy to manage1
- Easy to learn0
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Cons of DATOS
Cons of Google BigQuery
- You can't unit test changes in BQ data1
- Sdas0
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What is DATOS?
What is Google BigQuery?
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What companies use DATOS?
What companies use Google BigQuery?
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What tools integrate with DATOS?
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