Qubole vs Panoply: What are the differences?
Developers describe Qubole 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. On the other hand, Panoply is detailed as "Collect, combine, and integrate all your data with any analytics tools". It is the data warehouse built for analysts. Our data management platform automates all three key aspects of the data stack: data collection, management, and query optimization.
Qubole and Panoply belong to "Big Data as a Service" category of the tech stack.
Some of the features offered by Qubole are:
- Intuitive GUI
- Optimized Hive
- Improved S3 Performance
On the other hand, Panoply provides the following key features:
- Data warehouse
- Business Intelligence
- Optimized Query Engine
What is Panoply?
What is Qubole?
Need advice about which tool to choose?Ask the StackShare community!
Why do developers choose Panoply?
Why do developers choose Qubole?
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Panoply?
What are the cons of using Qubole?
What companies use Panoply?
Sign up to get full access to all the companiesMake informed product decisions
Sign up to get full access to all the tool integrationsMake informed product decisions
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