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Learn MorePros of Amazon Redshift
Pros of Google BigQuery
Pros of Myria
Pros of Amazon Redshift
- Data Warehousing41
- Scalable27
- SQL17
- Backed by Amazon14
- Encryption5
- Cheap and reliable1
- Isolation1
- Best Cloud DW Performance1
- Fast columnar storage1
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
Pros of Myria
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Cons of Amazon Redshift
Cons of Google BigQuery
Cons of Myria
Cons of Amazon Redshift
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Cons of Google BigQuery
- You can't unit test changes in BQ data1
- Sdas0
Cons of Myria
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What is Amazon Redshift?
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
What is Google BigQuery?
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.
What is Myria?
Myria is a distributed, shared-nothing Big Data management system and Cloud service from the University of Washington. We derive requirements from real users and complex workflows, especially in science.
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What companies use Amazon Redshift?
What companies use Google BigQuery?
What companies use Myria?
What companies use Google BigQuery?
What companies use Myria?
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What tools integrate with Amazon Redshift?
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What tools integrate with Myria?
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What are some alternatives to Amazon Redshift, Google BigQuery, and Myria?
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Amazon Redshift Spectrum
With Redshift Spectrum, you can extend the analytic power of Amazon Redshift beyond data stored on local disks in your data warehouse to query vast amounts of unstructured data in your Amazon S3 “data lake” -- without having to load or transform any data.
Hadoop
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.
Microsoft Azure
Azure is an open and flexible cloud platform that enables you to quickly build, deploy and manage applications across a global network of Microsoft-managed datacenters. You can build applications using any language, tool or framework. And you can integrate your public cloud applications with your existing IT environment.