Alooma vs Qubole: What are the differences?
Developers describe Alooma as "Integrate any data source like databases, applications, and any API - with your own Amazon Redshift". Get the power of big data in minutes with Alooma and Amazon Redshift. Simply build your pipelines and map your events using Alooma’s friendly mapping interface. Query, analyze, visualize, and predict now. On the other hand, Qubole is detailed as "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.
Alooma and Qubole can be categorized as "Big Data as a Service" tools.
What is Alooma?
What is Qubole?
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Why do developers choose Alooma?
Why do developers choose Qubole?
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What are the cons of using Alooma?
What are the cons of using Qubole?
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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