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Prefect.io VS Google Cloud Dataflow

Compare Prefect.io VS Google Cloud Dataflow and see what are their differences

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

Prefect.io logo Prefect.io

Prefect offers modern workflow orchestration tools for building, observing & reacting to data pipelines efficiently.

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.
Not present
  • Google Cloud Dataflow Landing page
    Landing page //
    2023-10-03

Prefect.io videos

No Prefect.io videos yet. You could help us improve this page by suggesting one.

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Google Cloud Dataflow videos

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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 Prefect.io and Google Cloud Dataflow)

Prefect.io

Google Cloud Dataflow

Data Pipelines
100 100%
Data Pipelines
0% 0
Big Data
0 0%
Big Data
100% 100
Workflows
100 100%
Workflows
0% 0
Data Dashboard
0 0%
Data Dashboard
100% 100

User comments

Share your experience with using Prefect.io 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 Prefect.io and Google Cloud Dataflow

Prefect.io Reviews

Top 8 Apache Airflow Alternatives in 2024
Prefect, similarly to Airflow, is designed to help user orchestrate their workflows using Python. This service is web-based and could be easily set up with containerization tools, such as Docker, and deployed on the Kubernetes clusters. As a result, Prefect offers a high grade of scalability to its users, which might be of particular value to rapidly growing companies.
Source: blog.skyvia.com
10 Best Airflow Alternatives for 2024
Prefect blends the ease of the Cloud with the security of on-premises to satisfy the demands of businesses that need to install, monitor, and manage processes fast. It has helped businesses of all sizes realize the immediate financial benefits of being able to swiftly deploy, scale, and manage their processes. Unlike Apache Airflow’s heavily limited and verbose tasks,...
Source: hevodata.com

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.

Prefect.io mentions (0)

We have not tracked any mentions of Prefect.io yet. Tracking of Prefect.io recommendations started around Mar 2024.

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: over 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 / about 2 years ago
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What are some alternatives?

When comparing Prefect.io and Google Cloud Dataflow, you can also consider the following products

Hall Monitor - Hall Monitor brings all your apps - Stripe, Shopify, Twitter, Instagram, and more - into unified automated reports, delivered to Slack or your inbox.

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

Dagster - The cloud-native open source orchestrator for the whole development lifecycle, with integrated lineage and observability, a declarative programming model, and best-in-class testability.

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

AWS Step Functions - AWS Step Functions makes it easy to coordinate the components of distributed applications and microservices using visual workflows.

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

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