
Google Cloud Dataproc
Amazon EMR
HortonWorks Data Platform
Google BigQuery
Google Cloud Dataflow
Snowflake
Qubole
MapR Converged Data Platform
Diff Anything
Beyond Compare
Diff Anything chooses a comparison engine that understands the inputs. Text uses a focused side-by-side diff, JSON and other structured formats compare semantic paths, CSV can match rows by key, folders recurse with ignore rules, and images add pixel heatmaps, overlay, and blink views. Compared files never leave the computer. There are no accounts, cloud comparison services, analytics, or telemetry. CLI and Git difftool modes make the same comparison model available in scripts and source-control workflows.
Google Cloud Dataproc
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Diff Anything's answer:
Diff Anything is a local-first desktop comparison and merge application that selects a comparison model for the inputs. It supports focused text diffs, semantic paths for JSON and other structured formats, key-based CSV matching, recursive folder comparison with ignore rules, and image heatmap, overlay, and blink views. Compared files stay on the computer, with no account, cloud comparison service, analytics, or telemetry.
Diff Anything's answer:
Diff Anything is a fit when you need one private desktop workflow for mixed artifacts rather than only plain text. It can compare text, structured data, CSV, folders, archives, documents, API schemas, HTTP responses, images, and binaries locally. CLI and Git difftool modes also make the same comparison model available in scripts and source-control workflows.
Diff Anything's answer:
Diff Anything is primarily for developers comparing mixed release artifacts, teams reviewing configuration or API changes, and people who need to inspect sensitive local files without uploading their content or creating an account.
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: over 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 / over 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.
Beyond Compare - Beyond Compare allows you to compare files and folders.
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.