Altiscale vs Qubole: What are the differences?
Developers describe Altiscale as "Hadoop as a Service". we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning. 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.
Altiscale and Qubole can be primarily classified as "Big Data as a Service" tools.
Some of the features offered by Altiscale are:
- Hadoop Dialtone
- “Infinite” Hadoop
- A Proactive Hadoop Helpdesk
On the other hand, Qubole provides the following key features:
- Intuitive GUI
- Optimized Hive
- Improved S3 Performance
"Our data sci & analysts would scream if went back toEMR" is the primary reason why developers consider Altiscale over the competitors, whereas "Simple UI and autoscaling clusters" was stated as the key factor in picking Qubole.
What is Altiscale?
What is Qubole?
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Why do developers choose Altiscale?
Why do developers choose Qubole?
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What are the cons of using Altiscale?
What are the cons of using Qubole?
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What tools integrate with Altiscale?
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