Apache Spark Streaming vs. Google Cloud Dataflow

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Apache Spark Streaming
Score 8.7 out of 10
N/A
Apache Spark Streaming is a scalable fault-tolerant streaming processing system that natively supports both batch and streaming workloads.N/A
Google Cloud Dataflow
Score 8.0 out of 10
N/A
Google offers Cloud Dataflow, a managed streaming analytics platform for real-time data insights, fraud detection, and other purposes.N/A
Pricing
Apache Spark StreamingGoogle Cloud Dataflow
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Apache Spark StreamingGoogle Cloud Dataflow
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache Spark StreamingGoogle Cloud Dataflow
Top Pros

No answers on this topic

Top Cons

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Features
Apache Spark StreamingGoogle Cloud Dataflow
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Apache Spark Streaming
8.4
1 Ratings
4% above category average
Google Cloud Dataflow
7.5
1 Ratings
8% below category average
Real-Time Data Analysis8.01 Ratings8.01 Ratings
Visualization Dashboards9.01 Ratings00 Ratings
Data Ingestion from Multiple Data Sources9.01 Ratings8.01 Ratings
Low Latency8.01 Ratings8.01 Ratings
Integrated Development Tools8.01 Ratings00 Ratings
Data wrangling and preparation8.01 Ratings00 Ratings
Linear Scale-Out8.01 Ratings7.01 Ratings
Machine Learning Automation9.01 Ratings7.01 Ratings
Data Enrichment9.01 Ratings7.01 Ratings
Best Alternatives
Apache Spark StreamingGoogle Cloud Dataflow
Small Businesses
Amazon Kinesis
Amazon Kinesis
Score 8.2 out of 10
Amazon Kinesis
Amazon Kinesis
Score 8.2 out of 10
Medium-sized Companies
Confluent Platform
Confluent Platform
Score 7.5 out of 10
Confluent Platform
Confluent Platform
Score 7.5 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 7.8 out of 10
Spotfire Streaming
Spotfire Streaming
Score 7.8 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Apache Spark StreamingGoogle Cloud Dataflow
Likelihood to Recommend
9.0
(1 ratings)
8.0
(1 ratings)
User Testimonials
Apache Spark StreamingGoogle Cloud Dataflow
Likelihood to Recommend
Apache
Apache Spark Streaming is a tool that we are using for almost a year and is excellent in managing batch processing. It is user-friendly. Using it, we can even process our massive data in fractions of seconds. Its pricing is its other plus point. Only its In-memory processing is its demerit as it occupies a large memory.
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Google
Based on my experience, streaming / real time / machine learning / AI type of processing and batch processing which needs less transformation are very well suited. Work load that needs complex transformation / multiple hops gets very complicated to implement. New feature like Dataflow SQL option will come in handy for sql heavy users.
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Pros
Apache
  • It is amazing in solving complicated transformative logic.
  • It is straightforward to program.
  • It is a very quick tool.
  • It processes large data within a fraction of seconds.
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Google
  • Streaming, Real time work load
  • Batch processing
  • Auto scaling
  • flexible pricing
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Cons
Apache
  • There must be more documentation.
  • It is a profoundly complex tool.
  • Its in-memory processing consumes massive memory.
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Google
  • inbuild template options can be expanded
  • more data connector options
  • easy of use
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Alternatives Considered
Apache
Apache Spark Streaming stands above all the huge data transformative tools because of its speed of processing which was quite slow in Presto as it takes a lot of our time in the data processing. Spark, comfortably provides integration with Jupyter like notebook environment. and Spark's combination with Jupyter and Python results in enhancing the speed .
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Google
Google Cloud Dataproc Cloud Datafusion
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Return on Investment
Apache
  • Cost and time-effective tool for our business.
  • We can integrate with Jupyter with many conveniences.
  • Its high-speed data processing has proved beneficial for us.
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Google
  • cost saving from managing our own data center for ETL servers
  • consumption based pricing
  • with auto scaling feature, we were able to expand components to support work load
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ScreenShots