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Apache Flink vs Google Cloud Dataflow comparison

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Streaming Analytics
May 2022
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Pricing and Cost Advice
  • "This is an open-source platform that can be used free of charge."
  • "The solution is open-source, which is free."
  • "Apache Flink is open source so we pay no licensing for the use of the software."
  • "It's an open-source solution."
  • More Apache Flink Pricing and Cost Advice →

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    Questions from the Community
    Top Answer:It is user-friendly and the reporting is good.
    Top Answer:There is a learning curve. It takes time to learn. The initial setup is complex, it could be simplified.
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    Also Known As
    Google Dataflow
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    Apache Flink is an open-source batch and stream data processing engine. It can be used for batch, micro-batch, and real-time processing. Flink is a programming model that combines the benefits of batch processing and streaming analytics by providing a unified programming interface for both data sources, allowing users to write programs that seamlessly switch between the two modes. It can also be used for interactive queries.

    Flink can be used as an alternative to MapReduce for executing iterative algorithms on large datasets in parallel. It was developed specifically for large to extremely large data sets that require complex iterative algorithms.

    Flink is a fast and reliable framework developed in Java, Scala, and Python. It runs on the cluster that consists of data nodes and managers. It has a rich set of features that can be used out of the box in order to build sophisticated applications.

    Flink has a robust API and is ready to be used with Hadoop, Cassandra, Hive, Impala, Kafka, MySQL/MariaDB, Neo4j, as well as any other NoSQL database.

    Apache Flink Features

    • Distributed execution of streaming programs on clusters of computers
    • Support for multiple data sources and sinks: this includes Hadoop file systems, databases, and other data sources
    • Streaming SQL query engine with support for windowing functions
    • Low latency query execution in milliseconds
    • Runs in a distributed fashion: it can be deployed on multiple machines or nodes to increase performance and reliability of data processing pipelines.
    • Powerful API that supports both batch and streaming applications
    • Runs on clusters of commodity hardware with minimal configuration
    • Can be integrated with other technologies, such as Apache Spark for complex data mining

    Apache Flink Benefits

    • Ease of use: Flink has an intuitive API and provides high-level abstractions for handling data streams. Even beginners in the field can work with the platform with ease.
    • Fault tolerance: Flink can automatically detect and recover from failures in the system.
    • Scalability: Flink scales to thousands of nodes. It can run on clusters of any size and the user does not have to worry about managing the cluster.

    Reviews from Real Users

    Apache Flink stands out among its competitors for a number of reasons. Two major ones are its low latency and its user-friendly interface. PeerSpot users take note of the advantages of these features in their reviews:

    The head of data and analytics at a computer software company notes, “The top feature of Apache Flink is its low latency for fast, real-time data. Another great feature is the real-time indicators and alerts which make a big difference when it comes to data processing and analysis.”

    Ertugrul A., manager at a computer software company, writes, “It's usable and affordable. It is user-friendly and the reporting is good.

    Google Dataflow is a unified programming model and a managed service for developing and executing a wide range of data processing patterns including ETL, batch computation, and continuous computation. Cloud Dataflow frees you from operational tasks like resource management and performance optimization.
    Learn more about Apache Flink
    Learn more about Google Cloud Dataflow
    Sample Customers
    LogRhythm, Inc., Inter-American Development Bank, Scientific Technologies Corporation, LotLinx, Inc., Benevity, Inc.
    Absolutdata, Backflip Studios, Bluecore, Claritics, Crystalloids, Energyworx, GenieConnect, Leanplum, Nomanini, Redbus, Streak, TabTale
    Top Industries
    Computer Software Company24%
    Comms Service Provider18%
    Financial Services Firm12%
    Media Company10%
    Comms Service Provider20%
    Computer Software Company19%
    Financial Services Firm11%
    Company Size
    Small Business22%
    Midsize Enterprise11%
    Large Enterprise67%
    Small Business16%
    Midsize Enterprise13%
    Large Enterprise71%
    Small Business16%
    Midsize Enterprise15%
    Large Enterprise69%
    Buyer's Guide
    Streaming Analytics
    May 2022
    Find out what your peers are saying about Databricks, Amazon, Solace and others in Streaming Analytics. Updated: May 2022.
    607,127 professionals have used our research since 2012.

    Apache Flink is ranked 4th in Streaming Analytics with 9 reviews while Google Cloud Dataflow is ranked 11th in Streaming Analytics. Apache Flink is rated 7.6, while Google Cloud Dataflow is rated 0.0. The top reviewer of Apache Flink writes "Scalable framework for stateful streaming aggregations". On the other hand, Apache Flink is most compared with Amazon Kinesis, Spring Cloud Data Flow, Azure Stream Analytics, Databricks and Apache Pulsar, whereas Google Cloud Dataflow is most compared with Apache NiFi, Amazon Kinesis, Databricks, Azure Stream Analytics and Amazon MSK.

    See our list of best Streaming Analytics vendors.

    We monitor all Streaming Analytics reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.