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Google Cloud Dataproc VS Send

Compare Google Cloud Dataproc VS Send and see what are their differences

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Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

Send logo Send

Instant messaging meets email (by Microsoft)
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09
  • Send Landing page
    Landing page //
    2023-09-30

Google Cloud Dataproc videos

+ Add

Dataproc

Send videos

+ Add

ArkTalks | How do we get from the SEND review to the system we need?

More videos:

  • Review - New Reviews Emails + Bulk Send Review Requests!
  • Tutorial - How to Get Your Google Review Link To Send To Customers.

Category Popularity

0-100% (relative to Google Cloud Dataproc and Send)

Google Cloud Dataproc

Send

Data Dashboard
100 100%
Data Dashboard
0% 0
File Sharing
0 0%
File Sharing
100% 100
Big Data
100 100%
Big Data
0% 0
Cloud Storage
0 0%
Cloud Storage
100% 100

User comments

Share your experience with using Google Cloud Dataproc and Send. For example, how are they different and which one is better?
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Social recommendations and mentions

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.

Google Cloud Dataproc mentions (3)

  • Connecting IPython notebook to spark master running in different machines
    I have also a spark cluster created with google cloud dataproc. Source: about 1 year ago
  • Why we don’t use Spark
    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 2 years ago
  • Data processing issue
    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 2 years ago

Send mentions (0)

We have not tracked any mentions of Send yet. Tracking of Send recommendations started around Mar 2021.

What are some alternatives?

When comparing Google Cloud Dataproc and Send, you can also consider the following products

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

Onionshare - OnionShare lets you securely and anonymously share a file of any size with someone.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

ShareDrop - HTML5 clone of Apple's AirDrop - easy P2P file transfer powered by WebRTC

Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.‎What is Apache Spark?

Send Anywhere - Send whatever you want, wherever you want

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