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Apache Flink VS FME by Safe

Compare Apache Flink VS FME by Safe and see what are their differences

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Apache Flink logo Apache Flink

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

FME by Safe logo FME by Safe

FME is an integrated collection of Spatial ETL tools for data transformation and data translation.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • FME by Safe Landing page
    Landing page //
    2023-04-25

Apache Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

FME by Safe features and specs

No features have been listed yet.

Analysis of Apache Flink

Overall verdict

  • Yes, Apache Flink is considered a good distributed stream processing framework.

Why this product is good

  • Rich api
    Flink offers a rich set of APIs for various levels of abstraction, catering to different needs of developers.
  • Scalability
    Flink provides excellent horizontal scalability, making it suitable for handling large data streams and high-throughput applications.
  • Fault tolerance
    Flink's checkpointing mechanism ensures fault-tolerance, maintaining data state consistency even after failures.
  • Ease of integration
    Flink integrates well with other big data tools and ecosystems, facilitating broader data architecture designs.
  • Real-time processing
    It excels at processing data in real-time, allowing for immediate insights and action on streaming data.
  • Community and support
    Being a part of the Apache Software Foundation, Flink benefits from a large community and comprehensive documentation.
  • Complex event processing
    It supports complex event processing, which is essential for many real-time applications.

Recommended for

  • real-time analytics
  • stream data processing
  • complex event processing
  • machine learning in streaming applications
  • applications requiring high-throughput and low-latency processing
  • companies looking for robust fault-tolerance in distributed systems

Apache Flink videos

+ Add

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

FME by Safe videos

+ Add

https://engage.safe.com/training/recorded/

Category Popularity

0-100% (relative to Apache Flink and FME by Safe)

Apache Flink

FME by Safe

Big Data
86 86%
Big Data
14% 14
Stream Processing
100 100%
Stream Processing
0% 0
Databases
76 76%
Databases
24% 24
Data Warehousing
0 0%
Data Warehousing
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Flink seems to be a lot more popular than FME by Safe. While we know about 41 links to Apache Flink, we've tracked only 3 mentions of FME by Safe. 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.

Apache Flink mentions (41)

  • What is Apache Flink? Exploring Its Open Source Business Model, Funding, and Community
    Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 19 days ago
  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / about 1 month ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / about 1 month ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / about 1 month ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / about 2 months ago
View more

FME by Safe mentions (3)

  • Where can I learn the basics of FME and ETL in GIS?
    Safe.com has all the resources you could ever imagine. Safe also offers a free at home license. Source: over 2 years ago
  • Best paid ELT tool for a startup
    We have had a lot of success with FME from safe.com. Covers all your reqs. You can get a decent free trail and have a cloud version also. Top of my head its around £800 per licence - alongside there ifra server. We are exploring FME cloud at the moment which will give us a PAYG option. Source: over 2 years ago
  • Everything about Google Chrome’s Latest Update: Version 90
    In the competition for (HTTP:// vs HTTPS://), HTTPS certainly wins as it is a safer navigation option for users. This implies if you visit a website let us say ‘safe.com’ on your browser, Google will load the website as https://safe.com. Here, Google discards the usual http://safe.com completely making the ‘HTTPS’ default. - Source: dev.to / almost 4 years ago

What are some alternatives?

When comparing Apache Flink and FME by Safe, you can also consider the following products

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

Microsoft Azure Data Lake - Azure Data Lake is a real-time data processing and analytics solution that works across platforms and languages.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.

Amazon Redshift - Learn about Amazon Redshift cloud data warehouse.

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

Greenplum Database - Greenplum Database is an open source parallel data warehousing platform.

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