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Google Cloud Dataproc VS Pepperdata

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

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Google Cloud Dataproc logo Google Cloud Dataproc

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

Pepperdata logo Pepperdata

Pepperdata's software runs on existing Hadoop clusters to give operators predictability, capacity, and visibility for their Hadoop jobs.
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09
  • Pepperdata Landing page
    Landing page //
    2023-09-18

Google Cloud Dataproc videos

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Dataproc

Pepperdata videos

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Boost Spark AI workloads with Pepperdata

More videos:

  • Tutorial - How To Implement Cloud Observability Like A Pro | Pepperdata
  • Review - The ONLY Thing That Matters with Data – Ash Munshi, CEO @ Pepperdata | #InsightJam Panel Highlights

Category Popularity

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

Google Cloud Dataproc

Pepperdata

Data Dashboard
100 100%
Data Dashboard
0% 0
Monitoring Tools
0 0%
Monitoring Tools
100% 100
Big Data
100 100%
Big Data
0% 0
Application Performance Monitoring
0 0%
Application Performance Monitoring
100% 100

User comments

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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

Pepperdata mentions (0)

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

What are some alternatives?

When comparing Google Cloud Dataproc and Pepperdata, 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.

9 Spokes - 9 Spokes is a free data dashboard that connects your apps to identify powerful insights to deliver your business KPI's.

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

CySight - CySight is an artificial intelligence-based cyber network intelligence platform that provides enterprises with the right information at the right time to proactively prevent and detect cyber threats.

HortonWorks Data Platform - The Hortonworks Data Platform is a 100% open source distribution of Apache Hadoop that is truly...

Epsagon - Track costs and fix your serverless application.

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