Qubole vs Xplenty: What are the differences?
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; Xplenty: Code-free data integration, data transformation and ETL in the cloud. Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage. Once done processing, Xplenty allows you to connect with Amazon Redshift, SAP HANA and Google BigQuery. You can also store processed data back in your favorite relational database, cloud storage or key-value store.
Qubole and Xplenty 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, Xplenty provides the following key features:
- Xplenty provides you with an visual, intuitive interface to design your ETL data flows
- Xplenty lets you integrate data from a variety of data stores, such as Amazon RDS, MySQL, PostgreSQL, Microsoft SQL Server and MongoDB.
- Read and process data from cloud storage sources such as Amazon S3, Rackspace Cloud Files and IBM SoftLayer Object Storage
What is Qubole?
What is Xplenty?
Want advice about which of these to choose?Ask the StackShare community!
Why do developers choose Qubole?
Sign up to add, upvote and see more prosMake informed product decisions
What are the cons of using Qubole?
What are the cons of using Xplenty?
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