Link copied to clipboard # Google Cloud Dataflow vs Spark Streaming Comparison - What are their main differences? Share [ Export ](/compare/google-cloud-dataflow/spark-streaming/export.csv) Google Cloud DataflowSpark Streaming[+ Add Product](#) Reviews **Google Cloud Dataflow** [ 4.2/5(44) ](https://www.g2.com/products/google-cloud-dataflow/reviews#reviews) **Spark Streaming** [ 4.2/5(40) ](https://www.g2.com/products/spark-streaming/reviews#reviews) Pricing **Google Cloud Dataflow** No pricing available **Spark Streaming** No pricing available **Pricing Insights** from reviews Time to Implement **Google Cloud Dataflow** Not enough reviews yet **Spark Streaming** Not enough reviews yet Return on Investment **Google Cloud Dataflow** Not enough reviews yet **Spark Streaming** Not enough reviews yet Perceived Cost **Google Cloud Dataflow** $$$$$ **Spark Streaming** $$$$$ Average Discount **Google Cloud Dataflow** Not enough reviews yet **Spark Streaming** Not enough reviews yet Pros & Cons **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) **Spark Streaming** Not enough data Ratings Meets Requirements **Google Cloud Dataflow** 9.0 9.024 **Spark Streaming** 9.0 9.029 Ease of Use **Google Cloud Dataflow** 8.1 8.124 **Spark Streaming** 8.2 8.229 Ease of Setup **Google Cloud Dataflow** 7.9 7.97 **Spark Streaming** 7.6 7.69 Ease of Admin **Google Cloud Dataflow** 8.0 8.05 **Spark Streaming** 8.0 8.09 Quality of Support **Google Cloud Dataflow** 8.3 8.321 **Spark Streaming** 8.7 8.726 Has the product been a good partner in doing business? **Google Cloud Dataflow** 9.0 9.05 **Spark Streaming** 8.5 8.59 Product Direction (% positive) **Google Cloud Dataflow** 9.0 9.023 **Spark Streaming** 9.3 9.332 Features Event Stream Processing[Hide 5 FeaturesShow 5 Features](javascript:void(0);) 9.3 8 9.0 30 Data Data Processing 9.8(won by 0.6) 7 (There is a greater than 0.5 difference between this product's rating and its competitors) 9.2 28 Data Sources 9.6(won by 0.6) 8 (There is a greater than 0.5 difference between this product's rating and its competitors) 9.0 27 Integration 9.3(won by 0.5) 7 (There is a greater than 0.5 difference between this product's rating and its competitors) 8.8 27 Real-Time Processing 9.6(won by 0.6) 8 (There is a greater than 0.5 difference between this product's rating and its competitors) 9.0 28 Analytics Reporting & Analytics 8.3 5 8.8(won by 0.5) 28 (There is a greater than 0.5 difference between this product's rating and its competitors) Big Data Processing and Distribution[Hide 10 FeaturesShow 10 Features](javascript:void(0);) 8.2 15 Not enough data Database Real-Time Data Collection 8.3(won by default) 11 Not enough data Data Distribution 8.9(won by default) 11 Not enough data Data Lake 8.5(won by default) 10 Not enough data Integrations Hadoop Integration 6.9(won by default) 7 Not enough data Spark Integration 6.9(won by default) 8 Not enough data Platform Machine Scaling 8.8(won by default) 11 Not enough data Data Preparation 8.6(won by default) 12 Not enough data Spark Integration 6.9(won by default) 8 Not enough data Processing Cloud Processing 8.9(won by default) 12 Not enough data Workload Processing 9.2(won by default) 10 Not enough data 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 [![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% [![Spark Streaming](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_2986a90abde9fb618861f2052b30d907/spark-streaming.jpg "Spark Streaming")](https://www.g2.com/products/spark-streaming/reviews) Spark Streaming Small-Business(50 or fewer emp.) 32.4% Mid-Market(51-1000 emp.) 40.5% Enterprise(\> 1000 emp.) 27.0% Small-Business (50 or fewer emp.) 33.3% 32.4% Mid-Market (51-1000 emp.) 33.3% 40.5% Enterprise (\> 1000 emp.) 33.3% 27.0% Reviewers' Industry [![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% [![Spark Streaming](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_2986a90abde9fb618861f2052b30d907/spark-streaming.jpg "Spark Streaming")](https://www.g2.com/products/spark-streaming/reviews) Spark Streaming Information Technology and Services 21.6% Computer Software 18.9% Telecommunications 8.1% Education Management 8.1% Financial Services 8.1% Other 35.1% FAQs ## Google Cloud Dataflow vs Spark Streaming FAQs Generated using AI Last updated: August 15, 2026 ### What is the difference between Google Cloud Dataflow vs Spark Streaming? Google Cloud Dataflow and Spark Streaming are both rated 4.2/5 by G2 reviewers, but Google Cloud Dataflow is most popular with enterprise users and is noted for its fully managed, scalable infrastructure, while Spark Streaming is also enterprise-focused and praised for its horizontal scalability and integration with the Spark ecosystem. | [Google Cloud Dataflow](https://www.g2.com/products/google-cloud-dataflow/reviews) | [Spark Streaming](https://www.g2.com/products/spark-streaming/reviews) | | --- | --- | | 4.2/5 (45 reviews) | 4.2/5 (40 reviews) | | Enterprise | Enterprise | | 7.9 | 7.6 | | 8.3 | 8.7 | | Fully managed, scalable, and easy integration with Google Cloud services | Horizontally scalable, fault tolerant, and strong Spark ecosystem integration | ### How do the pricing models of Google Cloud Dataflow and Spark Streaming compare? G2 reviewers rate Spark Streaming higher on value, with a stronger Price/Cost satisfaction score than Google Cloud Dataflow. - **Google Cloud Dataflow:** In recent reviews, several reviewers cite high costs and the need for careful configuration to avoid unexpected charges. - **Spark Streaming:** Reviewers note that Spark Streaming can be resource-intensive, but do not cite cost as a primary concern; satisfaction with value is higher. - **Switching reasons:** Reviewers mention switching to Spark Streaming for better cost control and to avoid the higher charges associated with managed services like Dataflow. ### What are the best alternatives to Google Cloud Dataflow and Spark Streaming? The top three alternatives to Google Cloud Dataflow and Spark Streaming are Amazon Kinesis Data Streams, Databricks, and Apache Kafka. | 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) | Enterprise | Reviewers cite high costs and the need for careful configuration | Fully managed, scalable, and easy integration with Google Cloud services | | [Spark Streaming](https://www.g2.com/products/spark-streaming/reviews) | 4.2/5 (40) | Enterprise | Resource-intensive but higher value satisfaction | Horizontally scalable, fault tolerant, and strong Spark ecosystem integration | | [Amazon Kinesis Data Streams](https://www.g2.com/products/aws-amazon-kinesis-data-streams/reviews) | 4.3/5 (90) | Mid-Market | — | Real-time data streaming and integration with AWS ecosystem | | [Databricks](https://www.g2.com/products/databricks/reviews) | 4.6/5 (1366) | Enterprise | — | Unified analytics platform and collaborative workspace | | [Apache Kafka](https://www.g2.com/products/apache-kafka/reviews) | 4.5/5 (132) | Enterprise | — | High-throughput distributed messaging and event streaming | ### Which Big Data Processing and Distribution features should I prioritize when comparing Google Cloud Dataflow and Spark Streaming? Buyers should prioritize scalability, ease of setup, quality of support, integration capabilities, and cost management when comparing Google Cloud Dataflow and Spark Streaming. - **Scalability:** Google Cloud Dataflow is frequently cited for its fully managed, autoscaling infrastructure; Spark Streaming is praised for horizontal scalability and fault tolerance. - **Ease of Setup:** Google Cloud Dataflow scores 7.9, Spark Streaming 7.6 on Ease of Setup. - **Quality of Support:** Google Cloud Dataflow scores 8.3, Spark Streaming 8.7 on Quality of Support. - **Integration Capabilities:** Google Cloud Dataflow is noted for easy integration with Google Cloud services; Spark Streaming is recognized for integration within the Spark ecosystem. - **Cost Management:** Google Cloud Dataflow has recurring mentions of high costs and the need for careful configuration; Spark Streaming is noted as resource-intensive but with higher value satisfaction. ### What are the pros and cons of Google Cloud Dataflow vs Spark Streaming? Google Cloud Dataflow's headline strength is its fully managed, scalable infrastructure, while Spark Streaming's is its horizontal scalability and Spark ecosystem integration. - **Google Cloud Dataflow strengths:** Fully managed and scalable, easy integration with Google Cloud services, strong support for both batch and streaming data, autoscaling, and real-time monitoring (all-time mentions: 1 for each of analytics, ease of use, easy management, features, insights, integrations, real-time analytics, real-time processing, speed, streaming). - **Google Cloud Dataflow trade-offs:** High costs, complex configuration for new users, limited documentation, and learning curve (all-time mentions: 1 for each of cost management, expensive, installation difficulty, learning difficulty). - **Spark Streaming strengths:** Horizontally scalable, fault tolerant, strong integration with the Spark ecosystem, and efficient real-time data processing. - **Spark Streaming trade-offs:** Resource-intensive, complex setup, and not ideal for small datasets or applications. ### Is Google Cloud Dataflow or Spark Streaming better for small businesses? Google Cloud Dataflow is better suited for small businesses based on reviewer sentiment and market segment data. - **Google Cloud Dataflow:** While most popular with enterprise users, recent reviews highlight ease of use and management, making it accessible for small businesses with limited infrastructure resources. - **Spark Streaming:** Primarily used by enterprise reviewers, with feedback noting complexity and resource intensity, making it less ideal for small business environments. ### Which Big Data Processing and Distribution platform has better integrations? Google Cloud Dataflow and Spark Streaming are rated at parity for integrations, with both products receiving positive reviewer sentiment for integration capabilities. - **Google Cloud Dataflow:** Reviewers mention easy integration with Google Cloud services, including Pub/Sub, BigQuery, and Cloud Spanner. - **Spark Streaming:** Reviewers highlight integration within the Spark ecosystem and compatibility with data sources like Kafka and Delta Lake. ### How do Google Cloud Dataflow and Spark Streaming compare on customer support? Spark Streaming scores higher on Quality of Support, with a 0.4-point lead over Google Cloud Dataflow (8.7 vs 8.3). - **Google Cloud Dataflow:** Reviewers describe support as responsive and helpful, but some mention limited documentation and a need for more comprehensive resources. - **Spark Streaming:** Reviewers consistently praise support quality, noting helpful responses and strong community resources. ### Which is easier to implement, Google Cloud Dataflow or Spark Streaming? Google Cloud Dataflow and Spark Streaming score within 0.3 points on Ease of Setup (7.9 vs 7.6), indicating near parity. - **Google Cloud Dataflow:** Reviewers note that setup is straightforward for those familiar with Google Cloud, but new users may face a learning curve due to complex configuration and limited documentation. - **Spark Streaming:** Reviewers describe initial setup as complex, especially for those without prior Spark experience, but highlight that configuration becomes easier with familiarity. Alternatives **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) **Spark Streaming Alternatives** ![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) ![Confluent](https://images.g2crowd.com/uploads/product/image/thumb_square/thumb_square_b087379a1153e7d513f37c83481c8ced/confluent.png "Confluent") [ Confluent ](/products/confluent/reviews) ![SAS Viya](https://images.g2crowd.com/uploads/product/hd_favicon/bd7a361df879327ee92c1d048aada28e/sas-sas-viya.svg "SAS Viya") [ SAS Viya ](/products/sas-sas-viya/reviews) ![Aiven for Apache Kafka](https://images.g2crowd.com/uploads/product/hd_favicon/17ecc18568d89176504b094004a98292/aiven-for-apache-kafka.svg "Aiven for Apache Kafka") [ Aiven for Apache Kafka ](/products/aiven-for-apache-kafka/reviews) ## Google Cloud Dataflow vs Spark Streaming When assessing the two solutions, reviewers found Spark Streaming easier to use. However, reviewers felt that Google Cloud Dataflow is easier to set up and do business with overall. Both products were equally easy to administer. - Google Cloud Dataflow and Spark Streaming both meet the requirements of our reviewers at a comparable rate. - When comparing quality of ongoing product support, reviewers felt that Spark Streaming is the preferred option. - For feature updates and roadmaps, our reviewers preferred the direction of Spark Streaming over Google Cloud Dataflow.