Azure Stream Analytics vs. StreamSets DataOps Platform

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Azure Stream Analytics
Score 8.0 out of 10
N/A
Microsoft offers Azure Stream Analytics for IoT and connected devices, supporting real-time analytics and reporting.
$0.11
per hour with a 1 SU minimum
StreamSets
Score 8.1 out of 10
N/A
StreamSets in San Francisco offers their DataOps Platform, a subscription based streaming analytics platform including StreamSets Data Collector data source management, Control Hub for data movement architecture management, StreamSets Data Collector Edge IoT manager, DataFlow Performance Manager (DPM), and StreamSets Data Protector compliance (e.g. GDPR) compliance module.N/A
Pricing
Azure Stream AnalyticsStreamSets DataOps Platform
Editions & Modules
Standard
$0.11
per hour with a 1 SU minimum
Dedicated
$0.11
per hour with a 36 SU minimum
No answers on this topic
Offerings
Pricing Offerings
Azure Stream AnalyticsStreamSets
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional DetailsAzure Stream Analytics is priced by the number of Streaming Units provisioned. A Streaming Unit represents the amount of memory and compute allocated to your resources.
More Pricing Information
Community Pulse
Azure Stream AnalyticsStreamSets DataOps Platform
Top Pros
Top Cons
Features
Azure Stream AnalyticsStreamSets DataOps Platform
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Azure Stream Analytics
6.1
1 Ratings
28% below category average
StreamSets DataOps Platform
9.0
1 Ratings
11% above category average
Real-Time Data Analysis7.01 Ratings00 Ratings
Data Ingestion from Multiple Data Sources7.01 Ratings00 Ratings
Low Latency8.01 Ratings8.01 Ratings
Integrated Development Tools2.01 Ratings10.01 Ratings
Data wrangling and preparation7.01 Ratings10.01 Ratings
Linear Scale-Out5.01 Ratings00 Ratings
Data Enrichment7.01 Ratings10.01 Ratings
Visualization Dashboards00 Ratings7.01 Ratings
Best Alternatives
Azure Stream AnalyticsStreamSets DataOps Platform
Small Businesses
IBM Streams
IBM Streams
Score 9.0 out of 10
IBM Streams
IBM Streams
Score 9.0 out of 10
Medium-sized Companies
Confluent
Confluent
Score 7.4 out of 10
Confluent
Confluent
Score 7.4 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 7.9 out of 10
Spotfire Streaming
Spotfire Streaming
Score 7.9 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Azure Stream AnalyticsStreamSets DataOps Platform
Likelihood to Recommend
7.0
(1 ratings)
9.0
(1 ratings)
User Testimonials
Azure Stream AnalyticsStreamSets DataOps Platform
Likelihood to Recommend
Microsoft
Data enrichment is effectively done in stream analytics also checking the values with different functionality like windowing and group by clause is effectively working.
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StreamSets
Majorly for all Batch and Streaming Scenarios we are designing StreamSets pipelines, few best suited and tried out use cases below : 1. JDBC to ADLS data transfer based on source refresh frequency. 2. Kafka to GCS. 3. Kafka to Azure Event. 4. Hub HDFS to ADLS data transfer. 5. Schema generation to generate Avro. The easy to design Canvas, Scheduling Jobs, Fragment creation and utilization, an inbuilt wide range of Stage availability makes it an even more favorable tool for me to design data engineering pipelines.
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Pros
Microsoft
  • Routing of data from multiple inputs to multiple output
  • You create your own user define function.
  • Intermediate query is working very effectively.
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StreamSets
  • A easy to use canvas to create Data Engineering Pipeline.
  • A wide range of available Stages ie. Sources, Processors, Executors, and Destinations.
  • Supports both Batch and Streaming Pipelines.
  • Scheduling is way easier than cron.
  • Integration with Key-Vaults for Secrets Fetching.
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Cons
Microsoft
  • Code competency is not that much effective
  • Ml models can't be integrated with stream analytics
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StreamSets
  • Monitoring/Visualization can be improvised and enhanced a lot (e.g. to monitor a Job to see what happened 7 days back with data transfer).
  • The logging mechanism can be simplified (Logs can be filtered with "ERROR", "DEBUG", "ALL" etc but still takes some time to get familiar for understanding).
  • Auto Scalability for heavy load transfer (Taking much time for >5 million record transfer from JDBC to ADLS destination in Avro file transfer).
  • There should be a concept of creating Global variables which is missing.
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Alternatives Considered
Microsoft
Azure Stream Analytics is easy to implement and also to integrate compare to other services like iot analytics
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StreamSets
StreamSets is a one-stop solution to design Data engineering Pipelines and doesn't require deep Programming knowledge, It's so user-friendly that anyone in Team can contribute to the Idea of pipeline design. In Hadoop One has to be programming proficient to use its various components like Hive, HDFS, Kafka, etc but in StreamSets all these stages are built-in and ready to use with minor configuration.
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Return on Investment
Microsoft
  • Very nice roi while using it.
  • Multiple integration is the best functionality
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StreamSets
  • Simplified Improvised Overall data ingestion and Integration Process.
  • Support to various Hetrogenous Source systems like RDBMS< Kafka, Salesforce, Key Vault.
  • Secure, easy to launch Integration tool.
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ScreenShots