Myria vs Qubole: What are the differences?
Myria: Scalable Analytics-as-a-Service platform based on relational algebra. 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; Qubole: Prepare, integrate and explore Big Data in the cloud (Hive, MapReduce, Pig, Presto, Spark and Sqoop). Qubole is a cloud based service that makes big data easy for analysts and data engineers.
Myria and Qubole can be primarily classified as "Big Data as a Service" tools.
Myria is an open source tool with 97 GitHub stars and 37 GitHub forks. Here's a link to Myria's open source repository on GitHub.
What is Myria?
What is Qubole?
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Why do developers choose Myria?
Why do developers choose Qubole?
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What are the cons of using Myria?
What are the cons of using Qubole?
What companies use Myria?
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What tools integrate with Myria?
We ultimately migrated our Hadoop jobs to Qubole, a rising player in the Hadoop as a Service space. Given that EMR had become unstable at our scale, we had to quickly move to a provider that played well with AWS (specifically, spot instances) and S3. Qubole supported AWS/S3 and was relatively easy to get started on. After vetting Qubole and comparing its performance against alternatives (including managed clusters), we decided to go with Qubole