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Cloudera CDH VS Google Cloud Dataflow

Compare Cloudera CDH VS Google Cloud Dataflow and see what are their differences

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

Cloudera CDH logo Cloudera CDH

Imagine what your business could do if all your data were collected in one centralized, secure, fully-governed place that any department could access anytime.

Google Cloud Dataflow logo Google Cloud Dataflow

Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.
  • Cloudera CDH Landing page
    Landing page //
    2023-10-15
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Cloudera CDH

Categories
  • Data Dashboard
  • Big Data
  • Database Tools
  • Development
Website cloudera.com
Pricing URL Official Cloudera CDH Pricing
Edit details

Google Cloud Dataflow

Categories
  • Big Data
  • Data Dashboard
  • Data Warehousing
  • Data Management
Website cloud.google.com
Pricing URL-
Edit details

Cloudera CDH videos

+ Add

Introduction

Google Cloud Dataflow videos

+ Add

Introduction to Google Cloud Dataflow - Course Introduction

More videos:

  • Review - Serverless data processing with Google Cloud Dataflow (Google Cloud Next '17)
  • Review - Apache Beam and Google Cloud Dataflow

Category Popularity

0-100% (relative to Cloudera CDH and Google Cloud Dataflow)

Cloudera CDH

Google Cloud Dataflow

Big Data
12 12%
Big Data
88% 88
Data Dashboard
12 12%
Data Dashboard
88% 88
Development
100 100%
Development
0% 0
Data Warehousing
0 0%
Data Warehousing
100% 100

User comments

Share your experience with using Cloudera CDH and Google Cloud Dataflow. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Cloudera CDH and Google Cloud Dataflow

Cloudera CDH Reviews

We have no reviews of Cloudera CDH yet.
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Google Cloud Dataflow Reviews

Top 8 Apache Airflow Alternatives in 2024
Google Cloud Dataflow is highly focused on real-time streaming data and batch data processing from web resources, IoT devices, etc. Data gets cleansed and filtered as Dataflow implements Apache Beam to simplify large-scale data processing. Such prepared data is ready for analysis for Google BigQuery or other analytics tools for prediction, personalization, and other purposes.
Source: blog.skyvia.com

Social recommendations and mentions

Based on our record, Google Cloud Dataflow seems to be more popular. It has been mentiond 14 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.

Cloudera CDH mentions (0)

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

Google Cloud Dataflow mentions (14)

  • How do you implement CDC in your organization
    Imo if you are using the cloud and not doing anything particularly fancy the native tooling is good enough. For AWS that is DMS (for RDBMS) and Kinesis/Lamba (for streams). Google has Data Fusion and Dataflow . Azure hasData Factory if you are unfortunate enough to have to use SQL Server or Azure. Imo the vendored tools and open source tools are more useful when you need to ingest data from SaaS platforms, and... Source: about 1 year ago
  • Here’s a playlist of 7 hours of music I use to focus when I’m coding/developing. Post yours as well if you also have one!
    This sub is for Apache Beam and Google Cloud Dataflow as the sidebar suggests. Source: over 1 year ago
  • How are view/listen counts rolled up on something like Spotify/YouTube?
    I am pretty sure they are using pub/sub with probably a Dataflow pipeline to process all that data. Source: over 1 year ago
  • Best way to export several GCP datasets to AWS?
    You can run a Dataflow job that copies the data directly from BQ into S3, though you'll have to run a job per table. This can be somewhat expensive to do. Source: over 1 year ago
  • Why we don’t use Spark
    It was clear we needed something that was built specifically for our big-data SaaS requirements. Dataflow was our first idea, as the service is fully managed, highly scalable, fairly reliable and has a unified model for streaming & batch workloads. Sadly, the cost of this service was quite large. Secondly, at that moment in time, the service only accepted Java implementations, of which we had little knowledge... - Source: dev.to / almost 2 years ago
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What are some alternatives?

When comparing Cloudera CDH and Google Cloud Dataflow, you can also consider the following products

Google Cloud Dataproc - Managed Apache Spark and Apache Hadoop service which is fast, easy to use, and low cost

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

Platfora - BI and Analytics Platform

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

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

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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