Link copied to clipboard # Apache Storm vs Google Cloud Dataflow Comparison - What are their main differences? Share [ Export ](/compare/apache-storm/google-cloud-dataflow/export.csv) Apache StormGoogle Cloud Dataflow[+ Add Product](#) Reviews **Apache Storm** [ 3.7/5(12) ](https://www.g2.com/products/apache-storm/reviews#reviews) **Google Cloud Dataflow** [ 4.2/5(44) ](https://www.g2.com/products/google-cloud-dataflow/reviews#reviews) Pricing **Apache Storm** No pricing available **Google Cloud Dataflow** No pricing available **Pricing Insights** from reviews Time to Implement **Apache Storm** 1 month Based on 7 responses **Google Cloud Dataflow** Not enough reviews yet Return on Investment **Apache Storm** 10 months Based on 6 responses **Google Cloud Dataflow** Not enough reviews yet Perceived Cost **Apache Storm** Not enough reviews yet **Google Cloud Dataflow** $$$$$ Average Discount **Apache Storm** Not enough reviews yet **Google Cloud Dataflow** Not enough reviews yet Pros & Cons **Apache Storm** Not enough data **Google Cloud Dataflow** [ Analytics (1) ](https://www.g2.com/products/google-cloud-dataflow/reviews?filters%5Bsentiment_snippet%5D=1866910&qs=pros-and-cons#reviews)[ Ease of Use (1) ](https://www.g2.com/products/google-cloud-dataflow/reviews?filters%5Bsentiment_snippet%5D=1866521&qs=pros-and-cons#reviews)[ Cost Management (1) ](https://www.g2.com/products/google-cloud-dataflow/reviews?filters%5Bsentiment_snippet%5D=2034355&qs=pros-and-cons#reviews)[ Expensive (1) ](https://www.g2.com/products/google-cloud-dataflow/reviews?filters%5Bsentiment_snippet%5D=2034357&qs=pros-and-cons#reviews) Ratings Meets Requirements **Apache Storm** 7.7 7.78 **Google Cloud Dataflow** 9.0 9.024 Ease of Use **Apache Storm** 6.0 6.08 **Google Cloud Dataflow** 8.1 8.124 Ease of Setup **Apache Storm** 6.2 6.27 **Google Cloud Dataflow** 7.9 7.97 Ease of Admin **Apache Storm** 7.2 7.26 **Google Cloud Dataflow** 8.0 8.05 Quality of Support **Apache Storm** 7.1 7.18 **Google Cloud Dataflow** 8.3 8.321 Has the product been a good partner in doing business? **Apache Storm** 8.0 8.05 **Google Cloud Dataflow** 9.0 9.05 Product Direction (% positive) **Apache Storm** 4.2 4.28 **Google Cloud Dataflow** 9.0 9.023 Features Event Stream Processing[Hide 5 FeaturesShow 5 Features](javascript:void(0);) Not enough data 9.3 8 Data Data Processing Not enough data 9.8(won by default) 7 Data Sources Not enough data 9.6(won by default) 8 Integration Not enough data 9.3(won by default) 7 Real-Time Processing Not enough data 9.6(won by default) 8 Analytics Reporting & Analytics Not enough data 8.3(won by default) 5 Big Data Processing and Distribution[Hide 10 FeaturesShow 10 Features](javascript:void(0);) Not enough data 8.2 15 Database Real-Time Data Collection Not enough data 8.3(won by default) 11 Data Distribution Not enough data 8.9(won by default) 11 Data Lake Not enough data 8.5(won by default) 10 Integrations Hadoop Integration Not enough data 6.9(won by default) 7 Spark Integration Not enough data 6.9(won by default) 8 Platform Machine Scaling Not enough data 8.8(won by default) 11 Data Preparation Not enough data 8.6(won by default) 12 Spark Integration Not enough data 6.9(won by default) 8 Processing Cloud Processing Not enough data 8.9(won by default) 12 Workload Processing Not enough data 9.2(won by default) 10 Show 1 feature category with incomplete data Big Data[Hide 17 FeaturesShow 17 Features](javascript:void(0);) Not enough data Not enough data Building Reports Data Transformation Not enough data Not enough data Data Modeling Not enough data Not enough data WYSIWYG Report Design Not enough data Not enough data Integration APIs Not enough data Not enough data Real-Time Data Not enough data Not enough data Real-Time Data Not enough data Not enough data Third-Party Integrations Not enough data Not enough data Third-Party Integrations Not enough data Not enough data Platform Mobile User Support Not enough data Not enough data Customization Not enough data Not enough data User, Role, and Access Management Not enough data Not enough data Internationalization Not enough data Not enough data Sandbox / Test Environments Not enough data Not enough data Performance and Reliability Not enough data Not enough data Breadth of Partner Applications Not enough data Not enough data Mobile Access Not enough data Not enough data Metadata Management Not enough data Not enough data User Insights Reviewers' Company Size [![Apache Storm](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_b350900e1c1cde239f398145fc13d8f3/apache-storm.jpg "Apache Storm")](https://www.g2.com/products/apache-storm/reviews) Apache Storm Small-Business(50 or fewer emp.) 50.0% Mid-Market(51-1000 emp.) 16.7% Enterprise(\> 1000 emp.) 33.3% [![Google Cloud Dataflow](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_0c51d2c2e5f85fe45126eb818f748267/google-cloud-dataflow.png "Google Cloud Dataflow")](https://www.g2.com/products/google-cloud-dataflow/reviews) Google Cloud Dataflow Small-Business(50 or fewer emp.) 33.3% Mid-Market(51-1000 emp.) 33.3% Enterprise(\> 1000 emp.) 33.3% Small-Business (50 or fewer emp.) 50.0% 33.3% Mid-Market (51-1000 emp.) 16.7% 33.3% Enterprise (\> 1000 emp.) 33.3% 33.3% Reviewers' Industry [![Apache Storm](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_b350900e1c1cde239f398145fc13d8f3/apache-storm.jpg "Apache Storm")](https://www.g2.com/products/apache-storm/reviews) Apache Storm Hospital & Health Care 16.7% Online Media 8.3% Market Research 8.3% Machinery 8.3% Information Technology and Services 8.3% Other 50.0% [![Google Cloud Dataflow](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_0c51d2c2e5f85fe45126eb818f748267/google-cloud-dataflow.png "Google Cloud Dataflow")](https://www.g2.com/products/google-cloud-dataflow/reviews) Google Cloud Dataflow Computer Software 11.9% Internet 7.1% Entertainment 7.1% Higher Education 4.8% Hospital & Health Care 4.8% Other 64.3% FAQs ## Apache Storm vs Google Cloud Dataflow FAQs Generated using AI Last updated: August 15, 2026 ### What is the difference between Google Cloud Dataflow vs Apache Storm? Google Cloud Dataflow stands out for its higher reviewer satisfaction, easier setup, and stronger support compared to Apache Storm. | [Google Cloud Dataflow](https://www.g2.com/products/google-cloud-dataflow/reviews) | [Apache Storm](https://www.g2.com/products/apache-storm/reviews) | | --- | --- | | 4.2/5 (45 reviews) | 3.7/5 (12 reviews) | | — | — | | 7.9 | 6.2 | | 8.3 | 7.1 | | Ease of Use | — | ### How do the pricing models of Google Cloud Dataflow and Apache Storm compare? Google Cloud Dataflow is rated higher for value by reviewers, with a stronger Price/Cost satisfaction score than Apache Storm. - **Google Cloud Dataflow:** In recent reviews, several reviewers mention that while Dataflow is powerful and easy to use, it is considered expensive and requires careful cost management. - **Apache Storm:** Reviewers highlight that Apache Storm is free and open source, but note that its performance and complexity can lead to higher indirect costs in time and resources. ### What are the best alternatives to Google Cloud Dataflow and Apache Storm? The top three alternatives to Google Cloud Dataflow and Apache Storm are Databricks, Apache Kafka, and BigQuery. | Product | G2 Rating (reviews) | Largest Segment | Pricing Insight | Top Reviewer-Cited Strength | | --- | --- | --- | --- | --- | | [Google Cloud Dataflow](https://www.g2.com/products/google-cloud-dataflow/reviews) | 4.2/5 (45 reviews) | — | In recent reviews, reviewers note it is expensive but easy to use | Ease of Use | | [Apache Storm](https://www.g2.com/products/apache-storm/reviews) | 3.7/5 (12 reviews) | — | Reviewers highlight it is free and open source | — | | [Databricks](https://www.g2.com/products/databricks/reviews) | 4.6/5 (1366 reviews) | Enterprise | — | — | | [Apache Kafka](https://www.g2.com/products/apache-kafka/reviews) | 4.5/5 (132 reviews) | Enterprise | — | — | | [BigQuery](https://www.g2.com/products/google-cloud-bigquery/reviews) | 4.5/5 (1224 reviews) | Enterprise | — | — | ### Which Big Data Processing and Distribution features should I prioritize when comparing Google Cloud Dataflow and Apache Storm? Buyers should prioritize Ease of Use, Ease of Setup, Quality of Support, Meets Requirements, and Ease of Admin when comparing Google Cloud Dataflow and Apache Storm. - **Ease of Use:** Google Cloud Dataflow scores 8.1, Apache Storm scores 6.0. - **Ease of Setup:** Google Cloud Dataflow scores 7.9, Apache Storm scores 6.2. - **Quality of Support:** Google Cloud Dataflow scores 8.3, Apache Storm scores 7.1. - **Meets Requirements:** Google Cloud Dataflow scores 9.0, Apache Storm scores 7.7. - **Ease of Admin:** Google Cloud Dataflow scores 8.0, Apache Storm scores 7.2. ### What are the pros and cons of Google Cloud Dataflow vs Apache Storm? Google Cloud Dataflow's headline strength is ease of use, while Apache Storm's is its open-source flexibility. - **Google Cloud Dataflow strengths:** Reviewers highlight ease of use, easy management, real-time analytics, and strong integration with Google Cloud services. - **Google Cloud Dataflow trade-offs:** Reviewers note high cost, complex setup for new users, and limited documentation as trade-offs. - **Apache Storm strengths:** Reviewers cite its open-source nature, flexibility to use with any programming language, and suitability for real-time processing. - **Apache Storm trade-offs:** Reviewers mention performance challenges, complex thread tuning, difficult setup, and limited documentation and community support. ### Is Google Cloud Dataflow or Apache Storm better for small businesses? Google Cloud Dataflow is a better fit for small businesses based on reviewer sentiment and ease of use. - **Google Cloud Dataflow:** Reviewers consistently mention that Dataflow is easy to use and manage, making it accessible for small teams despite its higher cost. - **Apache Storm:** Reviewers note that while it is free and open source, its complexity and setup challenges make it less suitable for small businesses without dedicated technical resources. ### Which Big Data Processing and Distribution platform has better integrations? Google Cloud Dataflow is favored for integrations, with reviewers citing its ability to connect with multiple data sources and sinks. - **Google Cloud Dataflow:** In recent reviews, reviewers mention integrations with Cloud Pub/Sub, Kafka, and Cloud Spanner. - **Apache Storm:** No recent reviewer-cited integrations are named. ### How do Google Cloud Dataflow and Apache Storm compare on customer support? Google Cloud Dataflow outperforms Apache Storm on Quality of Support by a margin of 1.2 points (8.3 vs 7.1). - **Google Cloud Dataflow:** Reviewers describe support as responsive and helpful, with several noting positive experiences and high satisfaction. - **Apache Storm:** Reviewers report that support is less formal and documentation is limited, with some expressing challenges in finding help. ### Which is easier to implement, Google Cloud Dataflow or Apache Storm? Google Cloud Dataflow is easier to implement than Apache Storm, with a 1.7-point advantage in Ease of Setup (7.9 vs 6.2). - **Google Cloud Dataflow:** Reviewers highlight straightforward setup, especially for those familiar with Google Cloud, but note a learning curve for new users and limited documentation. - **Apache Storm:** Reviewers consistently mention a complicated and time-consuming setup process, with challenges in configuration and limited documentation. Alternatives **Apache Storm Alternatives** ![Google Cloud BigQuery](https://images.g2crowd.com/uploads/product/hd_favicon/875b8a68eca98ce3458f26e9dd34cdf9/google-cloud-bigquery.svg "Google Cloud BigQuery") [ BigQuery ](/products/google-cloud-bigquery/reviews) ![Microsoft SQL Server](https://images.g2crowd.com/uploads/product/hd_favicon/a8a99a96fda235658139f710592f8a53/microsoft-sql-server.svg "Microsoft SQL Server") [ MS SQL ](/products/microsoft-sql-server/reviews) ![Databricks](https://images.g2crowd.com/uploads/product/hd_favicon/135d1c9e39e19ef56dc8d0bf90fce20f/databricks.svg "Databricks") [ Databricks ](/products/databricks/reviews) ![Snowflake](https://images.g2crowd.com/uploads/product/hd_favicon/1544409170/snowflake.svg "Snowflake") [ Snowflake ](/products/snowflake/reviews) **Google Cloud Dataflow Alternatives** ![Databricks](https://images.g2crowd.com/uploads/product/hd_favicon/135d1c9e39e19ef56dc8d0bf90fce20f/databricks.svg "Databricks") [ Databricks ](/products/databricks/reviews) ![Apache Kafka](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_809aa88d3571ee805a47d8fb156ba412/apache-kafka.jpg "Apache Kafka") [ Apache Kafka ](/products/apache-kafka/reviews) ![Amazon Kinesis Data Streams](https://images.g2crowd.com/uploads/product/hd_favicon/5383be31b099738701f86724a8b5cf9a/aws-amazon-kinesis-data-streams.svg "Amazon Kinesis Data Streams") [ Amazon Kinesis Data Streams ](/products/aws-amazon-kinesis-data-streams/reviews) ![Snowflake](https://images.g2crowd.com/uploads/product/hd_favicon/1544409170/snowflake.svg "Snowflake") [ Snowflake ](/products/snowflake/reviews) ## Apache Storm vs Google Cloud Dataflow When assessing the two solutions, reviewers found Google Cloud Dataflow easier to use, set up, and administer. Reviewers also preferred doing business with Google Cloud Dataflow overall. - Reviewers felt that Google Cloud Dataflow meets the needs of their business better than Apache Storm. - When comparing quality of ongoing product support, reviewers felt that Google Cloud Dataflow is the preferred option. - For feature updates and roadmaps, our reviewers preferred the direction of Google Cloud Dataflow over Apache Storm.