Qubole Demo On-Demand: Helping Data Engineers Operationalize Complex Streaming

This webinar demonstrated how Qubole Pipelines Service helps Data Engineers to operationalize complex streaming ETL workloads. We showed how it helps in moving data with transformations and in real-time from sources such as Kafka and Kinesis to targets such as S3, HIVE, and Snowflake.

Watch this webinar to see a demonstration of how you can operationalize complex streaming and benefit from:

  • Lower TCO at high performance: Qubole’s Spark Structured Streaming-as-a-service with advanced auto-scaling capabilities and reliability with exactly one semantics.
  • Higher Productivity: A management platform to build, test, deploy, monitor, and manage streaming ETL pipelines.
  • Wide Connectivity: Lower Time-to-Insight with a wide range of connectivity to various Real-Time, NoSQL, Data Warehouse stores to support end-to-end real-time analytics.
  • Open Source standard conformity and Multi-Cloud: To future-proof your solution, associate your workloads to OSS standards which can be seamlessly ported from one public cloud to another.

In addition to this, we demonstrated how to:

  • Drive down the costs of your big data workloads by 50%
  • Utilize Qubole for your data engineering, analytics, and data science use cases
  • Increase efficiency by leveraging cloud technologies that match your workflows
  • Extract more value with Machine Learning and AI
  • Optimize Apache Spark, Presto, Hadoop/Hive, and Airflow usage
  • Use Jupyter and/or Zeppelin Notebooks with Qubole

Explore Qubole and get answers to the big data, analytics, and machine learning questions that are important to you.