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Spark Streaming

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Last updated on

Ratings

G2
4.2/5
(40)

Spark Streaming description

Spark Streaming is a software tool that lets you analyze data in real-time. Imagine it like a live data processing engine, continuously taking in data from various sources like social media feeds or website traffic. It's particularly useful for tasks like fraud detection or monitoring online trends. Spark Streaming processes the data in small, manageable chunks, allowing for quick analysis and results. This makes it a powerful tool for businesses that need to react to changing data instantly.


Who is Spark Streaming best for

Spark Streaming is a real-time data processing tool ideal for large datasets. Users praise its scalability and real-time analytics capabilities but note potential performance limitations due to microbatching. It's a powerful solution for data engineers and scientists in industries requiring rapid data analysis.

  • Best for medium to large enterprises (100+ employees).

  • Well-suited for the finance, telecommunications, and tech industries.


Spark Streaming features

Supported

Spark Streaming ingests data in real time but is now a legacy system.

Supported

Spark Streaming offers real-time processing but with micro-batching latency. For instant processing, explore Continuous Processing mode.

Supported

Spark Streaming supports real-time data streaming with Kafka.

Supported

Spark Streaming supports real-time analytics but is now a legacy project.


Spark Streaming reviews

We've summarised 40 Spark Streaming reviews (Spark Streaming G2 reviews) and summarised the main points below.

Pros of Spark Streaming
  • Excellent for building large-scale data pipelines.
  • Handles large volumes of data efficiently with horizontal scalability and fault tolerance.
  • Enables real-time analytics and fast data processing.
  • Supports batch streaming for improved speed.
  • Easy-to-use API and intuitive programming model.
  • Seamless integration with the Spark ecosystem and various data sources.
Cons of Spark Streaming
  • Microbatching latency can reduce overall performance.
  • Resource-intensive, consuming a large amount of resources.
  • Complex setup and configuration can be challenging.
  • Limited compatibility with certain platforms.
  • Debugging and troubleshooting can be difficult.
  • Lack of built-in support for event time processing.
  • Suboptimal file management system.
  • Can be costly without proper cluster optimization.

Spark Streaming alternatives

  • Logo of Apache Flink
    Apache Flink
    Streamlines complex data processing for fast, consistent insights.
    Read more
  • Logo of SAS Event Stream Processing
    SAS Event Stream Processing
    Analyzes fast data in real time for quick, smart decisions.
    Read more
  • Logo of Azure Databricks
    Azure Databricks
    Unified analytics platform for massive data insights and AI.
    Read more
  • Logo of Apache Apex
    Apache Apex
    Unified, open-source big data stream and batch processing.
    Read more
  • Logo of LUX
    LUX
    Explore data visually, get real-time insights, and improve decisions.
    Read more
  • Logo of Amazon Kinesis
    Amazon Kinesis
    Real-time data streaming for instant insights and reactions.
    Read more

Spark Streaming FAQ

  • What is Spark Streaming and what does Spark Streaming do?

    Spark Streaming is a real-time data processing engine, ingesting data from diverse sources like social media and websites. It processes data in manageable micro-batches enabling rapid analysis, making it ideal for tasks like fraud detection and trend monitoring. However, it's now considered a legacy system.

  • How does Spark Streaming integrate with other tools?

    Spark Streaming integrates with various data sources like Kafka, Flume, and Kinesis, and processing engines like Hadoop and Hive. It seamlessly fits within the Spark ecosystem, leveraging other Spark components for storage and processing. This allows for efficient real-time data ingestion, analysis, and storage.

  • What the main competitors of Spark Streaming?

    Top alternatives to Spark Streaming include SAS Event Stream Processing, Hevo Data, LUX, and Tableau. These platforms offer similar real-time data processing capabilities for various data sources and volumes. They often provide more user-friendly interfaces and advanced analytics features.

  • Is Spark Streaming legit?

    Spark Streaming is a legitimate, albeit legacy, real-time data processing tool. While reliable for large-scale data pipelines and real-time analytics, users note micro-batching latency and resource intensiveness as potential drawbacks. Consider newer continuous processing alternatives for optimal performance.

  • How much does Spark Streaming cost?

    Spark Streaming is an open-source component of Apache Spark and does not have its own separate pricing. The cost depends on the underlying infrastructure used to run it.

  • Is Spark Streaming customer service good?

    There is no information available about Spark Streaming's customer service. However, users appreciate its scalability, real-time analytics capabilities, and easy-to-use API. Some find its resource intensiveness and complex setup challenging.


Reviewed by

MK
Michal Kaczor
CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

TT
Tymon Terlikiewicz
CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.