Apache Flink VS Scio

Compare Apache Flink vs Scio and see what are their differences.

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Apache Flink Scio
9 7
23,039 2,516
1.3% 0.4%
9.9 9.6
about 22 hours ago 5 days ago
Java Scala
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

Apache Flink

Posts with mentions or reviews of Apache Flink. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-12-15.
  • First 15 Open Source Advent projects
    16 projects | dev.to | 15 Dec 2023
    7. Apache Flink | Github | tutorial
  • I keep getting build failure when I try to run mvn clean compile package
    2 projects | /r/AskProgramming | 8 Apr 2023
    I'm trying to use https://github.com/mauricioaniche/ck to analyze the ck metrics of https://github.com/apache/flink. I have the latest version of java downloaded and I have the latest version of apache maven downloaded too. My environment variables are set correctly. I'm in the correct directory as well. However, when I run mvn clean compile package in powershell it always says build error. I've tried looking up the errors but there's so many. https://imgur.com/a/Zk8Snsa I'm very new to programming in general so any suggestions would be appreciated.
  • We Are Changing the License for Akka
    6 projects | news.ycombinator.com | 7 Sep 2022
  • DeWitt Clause, or Can You Benchmark %DATABASE% and Get Away With It
    21 projects | dev.to | 2 Jun 2022
    Apache Drill, Druid, Flink, Hive, Kafka, Spark
  • Computation reuse via fusion in Amazon Athena
    2 projects | news.ycombinator.com | 20 May 2022
    It took me some time to get a good grasp of the power of SQL; and it really kicked in when I learned about optimization rules. It's a program that you rewrite, just like an optimizing compiler would.

    You state what you want; you have different ways to fetch and match and massage data; and you can search through this space to produce a physical plan. Hopefully you used knowledge to weight parts to be optimized (table statistics, like Java's JIT would detect hot spots).

    I find it fascinating to peer through database code to see what is going on. Lately, there's been new advances towards streaming databases, which bring a whole new design space. For example, now you have latency of individual new rows to optimize for, as opposed to batch it whole to optimize the latency of a dataset. Batch scanning will be benefit from better use of your CPU caches.

    And maybe you could have a hybrid system which reads history from a log and aggregates in a batched manner, and then switches to another execution plan when it reaches the end of the log.

    If you want to have a peek at that here are Flink's set of rules [1], generic and stream-specific ones. The names can be cryptic, but usually give a good sense of what is going on. For example: PushFilterIntoTableSourceScanRule makes the WHERE clause apply the earliest possible, to save some CPU/network bandwidth further down. PushPartitionIntoTableSourceScanRule tries to make a fan-out/shuffle happen the earliest possible, so that parallelism can be made use of.

    [1] https://github.com/apache/flink/blob/5f8fb304fb5d68cdb0b3e3c...

  • Avro SpecificRecord File Sink using apache flink is not compiling due to error incompatible types: FileSink<?> cannot be converted to SinkFunction<?>
    3 projects | /r/apacheflink | 14 Sep 2021
    [1]: https://mvnrepository.com/artifact/org.apache.avro/avro-maven-plugin/1.8.2 [2]: https://github.com/apache/flink/blob/master/flink-connectors/flink-connector-files/src/main/java/org/apache/flink/connector/file/sink/FileSink.java [3]: https://ci.apache.org/projects/flink/flink-docs-master/docs/connectors/datastream/file_sink/ [4]: https://github.com/apache/flink/blob/c81b831d5fe08d328251d91f4f255b1508a9feb4/flink-end-to-end-tests/flink-file-sink-test/src/main/java/FileSinkProgram.java [5]: https://github.com/rajcspsg/streaming-file-sink-demo

Scio

Posts with mentions or reviews of Scio. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-14.
  • what popular companies uses Scala?
    3 projects | /r/scala | 14 May 2022
    Apache Beam API called Scio. They open sourced it https://spotify.github.io/scio/
  • Wanting to move away from SQL
    2 projects | /r/dataengineering | 25 Feb 2022
    I agree 100%. I haven't used SQL that much in previous data engineering roles, and I refuse to consider jobs that mostly deal with SQL. One of my roles involved using a nice Scala API for apache beam called Scio and it was great. Code was easy to write, maintain, and test. It also worked well with other services like PubSub and BigTable.
  • ETL Pipelines with Airflow: The Good, the Bad and the Ugly
    7 projects | news.ycombinator.com | 8 Oct 2021
    If you prefer Scala, then you can try Scio: https://github.com/spotify/scio.
  • ELT, Data Pipeline
    4 projects | dev.to | 1 Jan 2021
    To counter the above mentioned problem, we decided to move our data to a Pub/Sub based stream model, where we would continue to push data as it arrives. As fluentd is the primary tool being used in all our servers to gather data, rather than replacing it we leveraged its plugin architecture to use a plugin to stream data into a sink of our choosing. Initially our inclination was towards Google PubSub and Google Dataflow as our Data Scientists/Engineers use Big Query extensively and keeping the data in the same Cloud made sense. The inspiration of using these tools came from Spotify’s Event Delivery – The Road to the Cloud. We did the setup on one of our staging server with Google PubSub and Dataflow. Both didn't really work out for us as PubSub model requires a Subscriber to be available for the Topic a Publisher streams messages to, otherwise the messages are not stored. On top of it there was no way to see which messages are arriving. During this the weirdest thing that we encountered was that the Topic would be orphaned losing the subscribers when working with Dataflow. PubSub we might have managed to live with, the wall in our path was Dataflow. We started off with using SCIO from Spotify to work with Dataflow, there is a considerate lack of documentation over it and found the community to be very reserved on Github, something quite evident in the world of Scala for which they came up with a Code of Conduct for its user base to follow. Something that was required from Dataflow for us was to support batch write option to GCS, after trying our hand at Dataflow to no success to achieve that, Google's staff at StackOverflow were quite responsive and their response confirmed that it was something not available with Dataflow and streaming data to BigQuery, Datastore or Bigtable as a datastore was an option to use. The reason we didn't do that was to avoid high streaming cost to these services to store data, as majority of our jobs from the data team are based on batched hourly data. The initial proposal to the updated pipeline is shown below.

What are some alternatives?

When comparing Apache Flink and Scio you can also consider the following projects:

Trino - Official repository of Trino, the distributed SQL query engine for big data, formerly known as PrestoSQL (https://trino.io)

Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing

Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.

H2O - Sparkling Water provides H2O functionality inside Spark cluster

Apache Kafka - Mirror of Apache Kafka

Gearpump - Lightweight real-time big data streaming engine over Akka

Deep Java Library (DJL) - An Engine-Agnostic Deep Learning Framework in Java

Smile - Statistical Machine Intelligence & Learning Engine

Jupyter Scala - A Scala kernel for Jupyter

Weka