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Azure Stream Analytics VS StreamSets

Compare Azure Stream Analytics VS StreamSets and see what are their differences

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Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Azure Stream Analytics logo Azure Stream Analytics

Azure Stream Analytics offers real-time stream processing in the cloud.

StreamSets logo StreamSets

StreamSets provides Continuous Ingest technology for the next generation of big data applications.
  • Azure Stream Analytics Landing page
    Landing page //
    2023-01-21
  • StreamSets Landing page
    Landing page //
    2023-09-13

Azure Stream Analytics features and specs

  • Real-time Data Processing
    Azure Stream Analytics allows for real-time data processing, which enables businesses to analyze and process data as it is generated to make faster decisions.
  • Ease of Use
    The platform provides a simple and intuitive interface for setting up streaming jobs, making it accessible even for users with limited technical expertise.
  • Scalability
    It is designed to handle large volumes of data, allowing for automatic scaling to accommodate more data without compromising performance.
  • Integration with Azure Ecosystem
    Seamless integration with other Azure services like Azure Functions, Azure Event Hubs, and Azure Blob Storage allows for a unified cloud ecosystem.
  • Cost Efficiency
    Its pricing model based on the volume of data processed makes it cost-efficient, especially for projects that require variable or burst data processing.
  • Support for Multiple Input Sources
    It supports multiple input sources such as IoT Hub, Event Hub, and Azure Blob Storage, providing flexibility in designing the data flow architecture.

Possible disadvantages of Azure Stream Analytics

  • Limited Machine Learning Capabilities
    Azure Stream Analytics has limited built-in capabilities for complex machine learning models, requiring integration with other services for advanced analytics.
  • Complex Queries
    While powerful, the query language can be complex for users unfamiliar with SQL, potentially necessitating a learning curve for new users.
  • Geographic Availability
    Not all features are available in every Azure region, which may limit its usability for some global operations depending on the region's support.
  • Debugging and Monitoring
    Some users have reported that debugging and monitoring issues can be challenging due to limited tools compared to other more mature data processing platforms.
  • Dependency on Internet Connectivity
    As a cloud-based service, it requires reliable internet connectivity, which can be a constraint for operations in environments with unstable connections.

StreamSets features and specs

  • User-Friendly Interface
    StreamSets provides an intuitive and visually appealing interface for designing and managing data pipelines, making it accessible even for users without extensive coding experience.
  • Real-Time Data Processing
    The platform excels at real-time data ingestion, transformation, and delivery, enabling timely insights and immediate actions on streaming data.
  • Comprehensive Connectors
    StreamSets supports a wide range of data sources and destinations out of the box, including cloud services, databases, and big data platforms, ensuring versatility in data integration tasks.
  • Data Drift Management
    It offers robust features for detecting and managing data drift, helping maintain data quality and consistency over time as source schemas evolve.
  • Scalability
    StreamSets is designed to scale effortlessly with increasing data volumes and can handle large-scale data pipelines efficiently.

Possible disadvantages of StreamSets

  • Cost
    The pricing model can be expensive, particularly for small to mid-sized enterprises, making it less accessible for organizations with limited budgets.
  • Learning Curve
    Although the interface is user-friendly, mastering the platform's advanced features and configurations may require a significant learning curve.
  • Resource Intensive
    Running StreamSets can be resource-intensive, requiring substantial computational and memory resources, which may lead to higher operational costs.
  • Limited Custom Scripting
    While StreamSets offers many in-built functionalities, it provides limited scope for custom scripting compared to other data pipeline tools, which may restrict flexibility for complex custom tasks.
  • Dependency on Internet Connectivity
    For cloud-based deployments, the performance and reliability of StreamSets can be heavily dependent on internet connectivity, which could be a concern for organizations with unstable connections.

Azure Stream Analytics videos

+ Add

Azure Stream Analytics

More videos:

  • Review - Real-time Analytics with Azure Stream Analytics
  • Demo - Introduction to Azure Stream Analytics + Demo

StreamSets videos

+ Add

What is StreamSets Transformer?

More videos:

  • Review - Making Apache Kafka Dead Easy With StreamSets | DZone.com Webinar
  • Review - Power Your Delta Lake with Streaming Transactional Changes - Rupal Shah (StreamSets)

Category Popularity

0-100% (relative to Azure Stream Analytics and StreamSets)

Azure Stream Analytics

StreamSets

Stream Processing
100 100%
Stream Processing
0% 0
DevOps Tools
0 0%
DevOps Tools
100% 100
Data Management
100 100%
Data Management
0% 0
Continuous Integration And Delivery
0 0%
Continuous Integration And Delivery
100% 100

User comments

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Social recommendations and mentions

Based on our record, StreamSets seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Azure Stream Analytics mentions (0)

We have not tracked any mentions of Azure Stream Analytics yet. Tracking of Azure Stream Analytics recommendations started around Mar 2021.

StreamSets mentions (2)

  • Best way to automate JSON to CSV/Relational Tables at scale? Anyone have used Flexter?
    If you would like to take a look at https://streamsets.com/ the Data Collector product can handle this for you as well as dynamically generate the target tables. It has a number of functions to handle your JSON no matter the complexity. However, given the dynamic nature it may benefit to touch base so please feel free to chat or message me. Source: almost 3 years ago
  • Data engineering in reality
    StreamSets offers a free tier and free option for training. You can build, run, and manage your pipelines in one place. Source: about 3 years ago

What are some alternatives?

When comparing Azure Stream Analytics and StreamSets, you can also consider the following products

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

Packer - Packer is an open-source software for creating identical machine images from a single source configuration.

PieSync - Seamless two-way sync between your CRM, marketing apps and Google in no time

Puppet Enterprise - Get started with Puppet Enterprise, or upgrade or expand.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Terraform - Tool for building, changing, and versioning infrastructure safely and efficiently.

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