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Up.Time Software VS Google Cloud Dataproc

Compare Up.Time Software VS Google Cloud Dataproc and see what are their differences

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Contents:
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  2. » Videos
  3. » Reviews
  4. » Alternatives

Up.Time Software logo Up.Time Software

Explanatory video can be found here.

Google Cloud Dataproc logo Google Cloud Dataproc

Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost
  • Up.Time Software Landing page
    Landing page //
    2022-10-08
  • Google Cloud Dataproc Landing page
    Landing page //
    2023-10-09

Up.Time Software videos

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Google Cloud Dataproc videos

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Dataproc

Category Popularity

0-100% (relative to Up.Time Software and Google Cloud Dataproc)

Up.Time Software

Google Cloud Dataproc

Databases
100 100%
Databases
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100
Monitoring Tools
100 100%
Monitoring Tools
0% 0
Big Data
0 0%
Big Data
100% 100

User comments

Share your experience with using Up.Time Software and Google Cloud Dataproc. 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.

Up.Time Software mentions (0)

We have not tracked any mentions of Up.Time Software yet. Tracking of Up.Time Software recommendations started around Mar 2021.

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

What are some alternatives?

When comparing Up.Time Software and Google Cloud Dataproc, you can also consider the following products

TimescaleDB - TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.

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

KairosDB - Fast Time Series Database on Cassandra

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

VictoriaMetrics - Cost-effective database for huge amounts of time series data

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

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