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Amazon EMR
HortonWorks Data Platform
Google BigQuery
Google Cloud Dataflow
Snowflake
Qubole
MapR Converged Data Platform
Getwebstack
MarsX
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Google Cloud Dataproc
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Based on our record, Google Cloud Dataproc seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I have also a spark cluster created with google cloud dataproc. Source: about 3 years ago
Specifically, we heavily rely on managed services from our cloud provider, Google Cloud Platform (GCP), for hosting our data in managed databases like BigTable and Spanner. For data transformations, we initially heavily relied on DataProc - a managed service from Google to manage a Spark cluster. - Source: dev.to / about 4 years ago
With that, the best way to maximize processing and minimize time is to use Dataflow or Dataproc depending on your needs. These systems are highly parallel and clustered, which allows for much larger processing pipelines that execute quickly. Source: over 4 years ago
Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.
MarsX - MarsX leverages the power of AI to help users build mobile and web applications using code and no-code technology. MarsX is highly accessible, allowing even non-developers and those with zero building and coding experience to create their own mobile
HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
Snowflake - Snowflake is the only data platform built for the cloud for all your data & all your users. Learn more about our purpose-built SQL cloud data warehouse.