Google Cloud Dataflow vs Informatica Data Engineering Streaming comparison

Google and Informatica are both solutions in the Streaming Analytics category. Google is ranked #7 with an average rating of 8.0, while Informatica is ranked #16 with an average rating of 8.0. Google holds a 7.4% mindshare in SA, compared to Informatica’s 1.4% mindshare. Additionally, 92% of Google users are willing to recommend the solution, compared to 100% of Informatica users who would recommend it.

Google Cloud Dataflow

Read 13 Google Cloud Dataflow reviews

3,122 Views
2,513 Comparison Views

92% willing to recommend

Informatica Data Engineerin...

Read 1 Informatica Data Engineering Streaming review

410 Views
381 Comparison Views

100% willing to recommend

Google Cloud Dataflow

Informatica Data Engineerin...

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between Google Cloud Dataflow and Informatica Data Engineering Streaming based on real PeerSpot user reviews.

Find out what your peers are saying about Databricks, Amazon Web Services (AWS), Microsoft and others in Streaming Analytics.

To learn more, read our detailed Streaming Analytics Report (Updated: March 2025).

Buyer's Guide

Streaming Analytics

March 2025

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Helped 847,625 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Google Cloud Dataflow

Ranking in Streaming Analytics

7th

Average Rating

8.0

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

No ranking in other categories

Informatica Data Engineerin...

Ranking in Streaming Analytics

16th

Average Rating

8.0

Reviews Sentiment

6.4

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Google Cloud Dataflow is 7.4%, up from 7.0% compared to the previous year. The mindshare of Informatica Data Engineering Streaming is 1.4%, up from 0.9% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Streaming Analytics

Featured Reviews

Jana Polianskaja

Data Engineer at Accenture

Build Scalable Data Pipelines with Apache Beam and Google Cloud Dataflow

As a data engineer, I find several features of Google Cloud Dataflow particularly valuable. The ability to test solutions locally using Direct Runner is crucial for development, allowing me to validate pipelines without incurring the costs of full Dataflow jobs. The unified programming model for both batch and streaming processing is exceptional - requiring only minor code adjustments to optimize for either mode. This flexibility extends to language support, with robust implementations in both Java and Python, allowing teams to leverage their existing expertise. The platform's comprehensive monitoring capabilities are another standout feature. The intuitive interface, Grafana integration, and extensive service connectivity make troubleshooting and performance tracking highly efficient. Furthermore, seamless integration with Google Cloud Composer (managed Airflow) enables sophisticated orchestration of data pipelines.

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Reviewer43443

BI Practice Lead at a tech services company with 51-200 employees

Helps with real-time data processing and improves decision-making overall

It improves decision-making overall for the company. Informatica is usually the tool for setting up the data, streaming the data into your data warehouse from your source, transforming the data, and preparing and modeling it into some desired format. It improves the performance. You need to know how to use it and how to implement it, but it improves performance.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"Google's support team is good at resolving issues, especially with large data."

"The integration within Google Cloud Platform is very good."

"The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use."

"The support team is good and it's easy to use."

"The solution allows us to program in any language we desire."

"The best feature of Google Cloud Dataflow is its practical connectedness."

"It is a scalable solution."

"The service is relatively cheap compared to other batch-processing engines."

More Google Cloud Dataflow pros

"It improves the performance."

Cons

"Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job."

"The deployment time could also be reduced."

"I would like to see improvements in consistency and flexibility for schema design for NoSQL data stored in wide columns."

"There are certain challenges regarding the Google Cloud Composer which can be improved."

"I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool."

"Promoting the technology more broadly would help increase its adoption."

"Occasionally, dealing with a huge volume of data causes failure due to array size."

"When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs."

More Google Cloud Dataflow cons

"Skill requirement is required. There is a learning curve."

Pricing and Cost Advice

"Google Cloud Dataflow is a cheap solution."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate the solution's pricing a seven to eight out of ten."

"The solution is not very expensive."

"Google Cloud is slightly cheaper than AWS."

"The tool is cheap."

"The price of the solution depends on many factors, such as how they pay for tools in the company and its size."

"The solution is cost-effective."

"On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten."

Information not available

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Top Industries

By visitors reading reviews

Financial Services Firm

17%

Manufacturing Company

12%

Retailer

11%

Computer Software Company

11%

Financial Services Firm

24%

Manufacturing Company

15%

Computer Software Company

14%

Educational Organization

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

What do you like most about Google Cloud Dataflow?

The product's installation process is easy...The tool's maintenance part is somewhat easy.

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What is your experience regarding pricing and costs for Google Cloud Dataflow?

Pricing is normal. It is part of a package received from Google, and they are not charging us too high.

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What needs improvement with Google Cloud Dataflow?

I am not sure, as we built only one job, and it is running on a daily basis. Everything else is managed using BigQuery schedulers and Talend. However, occasionally, dealing with a huge volume of da...

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What needs improvement with Informatica Data Engineering Streaming?

Skill requirement is required. There is a learning curve.

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What is your primary use case for Informatica Data Engineering Streaming?

We implement business intelligence solutions, including data warehousing tools, data integration to load data into warehouses, and then creating reports.

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What advice do you have for others considering Informatica Data Engineering Streaming?

Overall, I would rate the solution an eight out of ten. Usually, Informatica is for big clients because of its pricing, and it also requires some skill sets. It requires investment into a proper da...

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Compared 11% of the time

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Product Reports

Buyer's Guide

Google Cloud Dataflow

April 2025

Download Google Cloud Dataflow product report

Buyer's Guide

Streaming Analytics

March 2025

Informatica Data Engineering Streaming report

Download Informatica Data Engineering Streaming product report

Also Known As

Google Dataflow

Big Data Streaming, Informatica Intelligent Streaming, Intelligent Streaming

Overview

Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.

Google

Informatica Intelligent Streaming allows organizations to prepare and process streams of data and uncover insights while acting in time to suit business needs. It can scale out horizontally and vertically to handle petabytes of data while honoring business service level agreements (SLAs). Intelligent Streaming provides pre-built high-performance connectors such as Kafka, HDFS, NoSQL databases, and enterprise messaging systems and data transformations to enable a code-free method of defining your data integration logic.

Informatica

Sample Customers

Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale

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