Comparing Data Lake Engineering Tools: Spark Platforms vs Upsolver

Apache Spark is a popular open-source framework for large-scale distributed data processing. Cloud-based platforms that offer a managed distribution of Spark are widely used for transforming data in cloud storage into analytics-ready data – but are they the right tool for the job?

In this detailed guide we’ll take a close look at Apache Spark and Spark-based platforms, and understand the pros and cons of these tools compared to Upsolver’s cloud-native data lake engineering solution.

Get the White Paper

Thanks! Get your ebook here
Download Now

Get the white paper now to learn:

  • Differences between Hadoop and Spark
  • Common use cases for Apache Spark and Spark-based platforms
  • Is it possible to achieve self-service with a Spark-based solution?
  • The Upsolver approach and how it differs from Apache Hadoop and Spark
  • Detailed comparison matrix between Spark and alternatives – features, pricing, functionality
upsolver vs spark ebook

Powering data lakes for data-intensive companies