Value and Innovation with Serverless Spark
Google Cloud Platform’s Dataproc Serverless is the industry’s first auto-scaling offering to run Spark workloads. It helps enterprises seamlessly handle big data processing without managing below-the-line infrastructure and only paying for the job run time, not the entire time the servers are up, opening new avenues of value and innovation. Discover features, business benefits, and best practices in this series of videos and blogs.
What is Serverless Spark?
Discover the power of serverless Spark, a revolutionary technology that eliminates the need for infrastructure management and delivers seamless scalability and cost-effectiveness for data processing and analytics.
Five ways enterprises can fire up innovation with Dataproc Serverless for running Spark workloads
Discover how enterprises can ignite innovation by leveraging the transformative capabilities of Dataproc Serverless to efficiently run Spark workloads, enabling scalable and cost-effective data processing with enhanced agility and reduced operational overhead.
What are the common workloads that can be migrated to Serverless Spark?
Explore the common workloads that can be seamlessly migrated to Serverless Spark, unlocking the power of distributed data processing with minimal infrastructure management.
How Google’s Dataproc Serverless for Spark compares with Databricks and AWS Glue
GCP Dataproc Serverless is better attuned for Spark workloads, given its NoOps essence, superlatively faster boot time, and zero infrastructure management.
What are the competitive products to Serverless Spark?
Explore alternative products to Serverless Spark, including Databricks Serverless and AWS Glue.
Choosing between Google Serverless Spark & Dataproc on GCE
Four factors that can help teams make the right decision based on the type of workload, need to control infrastructure, and cost parameters.
How long does it take to launch a Spark cluster?
Explore the startup times of Spark clusters on different platforms and discover ongoing efforts to minimize latency.
How Google’s Serverless Spark can successfully harmonize collaboration between data engineers and analysts in various industries
How Google Dataproc Serverless Spark offering fits across industry use cases.
