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Apache Flink VS Striim

Compare Apache Flink VS Striim 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.

Striim logo Striim

Striim provides an end-to-end, real-time data integration and streaming analytics platform.
  • Apache Flink Landing page
    Landing page //
    2023-10-03
  • Striim Landing page
    Landing page //
    2023-10-20

Apache Flink videos

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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

Striim videos

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Striim On Premise to Azure Integration Step 1

More videos:

  • Review - Tech review: AwoX Striim LED Light Bulb
  • Review - Striim On Premise to Azure Integration Step 2

Category Popularity

0-100% (relative to Apache Flink and Striim)

Apache Flink

Striim

Big Data
100 100%
Big Data
0% 0
Development
0 0%
Development
100% 100
Stream Processing
100 100%
Stream Processing
0% 0
Backup & Sync
0 0%
Backup & Sync
100% 100

User comments

Share your experience with using Apache Flink and Striim. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Apache Flink and Striim

Apache Flink Reviews

We have no reviews of Apache Flink yet.
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Striim Reviews

Top 14 ETL Tools for 2023
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets — including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop — in various file formats. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL or Java.
Source: www.integrate.io
Top 7 ETL Tools for 2021
Striim offers a real-time data integration platform for big data workloads. Users can integrate a wide variety of data sources and targets in roughly 20 different file formats, including Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, and Hadoop. Striim is compliant with data privacy regulations such as GDPR and HIPAA, and users can define pre-load transformations using SQL...
Source: www.xplenty.com
The 28 Best Data Integration Tools and Software for 2020
Description: Striim offers a real-time data integration solution that enables continuous query processing and streaming analytics. Striim integrates data from a wide variety of sources, including transaction/change data, events, log files, application and IoT sensor, and real-time correlation across multiple streams. The platform features pre-built data pipelines,...
Source: solutionsreview.com

Social recommendations and mentions

Based on our record, Apache Flink seems to be more popular. It has been mentiond 27 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.

Apache Flink mentions (27)

  • Top 10 Common Data Engineers and Scientists Pain Points in 2024
    Data scientists often prefer Python for its simplicity and powerful libraries like Pandas or SciPy. However, many real-time data processing tools are Java-based. Take the example of Kafka, Flink, or Spark streaming. While these tools have their Python API/wrapper libraries, they introduce increased latency, and data scientists need to manage dependencies for both Python and JVM environments. For example,... - Source: dev.to / 18 days ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / 3 months ago
  • Go concurrency simplified. Part 4: Post office as a data pipeline
    Also, this knowledge applies to learning more about data engineering, as this field of software engineering relies heavily on the event-driven approach via tools like Spark, Flink, Kafka, etc. - Source: dev.to / 4 months ago
  • Five Apache projects you probably didn't know about
    Apache SeaTunnel is a data integration platform that offers the three pillars of data pipelines: sources, transforms, and sinks. It offers an abstract API over three possible engines: the Zeta engine from SeaTunnel or a wrapper around Apache Spark or Apache Flink. Be careful, as each engine comes with its own set of features. - Source: dev.to / 4 months ago
  • Getting Started with Flink SQL, Apache Iceberg and DynamoDB Catalog
    Due to the technology transformation we want to do recently, we started to investigate Apache Iceberg. In addition, the data processing engine we use in house is Apache Flink, so it's only fair to look for an experimental environment that integrates Flink and Iceberg. - Source: dev.to / 4 months ago
View more

Striim mentions (0)

We have not tracked any mentions of Striim yet. Tracking of Striim recommendations started around Mar 2021.

What are some alternatives?

When comparing Apache Flink and Striim, 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.

HVR - Your data. Where you need it. HVR is the leading independent real-time data replication solution that offers efficient data integration for cloud and more.

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

Oracle Data Integrator - Oracle Data Integrator is a data integration platform that covers batch loads, to trickle-feed integration processes.

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

Bryteflow Data Replication and Integration - Bryteflow is a popular platform that offers many services, including data replication and integration.

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