Software Alternatives & Reviews

Talend Big Data Platform VS Apache Beam

Compare Talend Big Data Platform VS Apache Beam and see what are their differences

Talend Big Data Platform logo Talend Big Data Platform

Talend Big Data Platform is a data integration and data quality platform built on Spark for cloud and on-premises.

Apache Beam logo Apache Beam

Apache Beam provides an advanced unified programming model to implement batch and streaming data processing jobs.
  • Talend Big Data Platform Landing page
    Landing page //
    2023-01-19
  • Apache Beam Landing page
    Landing page //
    2022-03-31

Talend Big Data Platform videos

No Talend Big Data Platform videos yet. You could help us improve this page by suggesting one.

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Apache Beam videos

How to Write Batch or Streaming Data Pipelines with Apache Beam in 15 mins with James Malone

More videos:

  • Review - Best practices towards a production-ready pipeline with Apache Beam
  • Review - Streaming data into Apache Beam with Kafka

Category Popularity

0-100% (relative to Talend Big Data Platform and Apache Beam)
Data Integration
100 100%
0% 0
Big Data
0 0%
100% 100
ETL
100 100%
0% 0
Data Dashboard
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Apache Beam seems to be more popular. It has been mentiond 14 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.

Talend Big Data Platform mentions (0)

We have not tracked any mentions of Talend Big Data Platform yet. Tracking of Talend Big Data Platform recommendations started around Mar 2021.

Apache Beam mentions (14)

  • Ask HN: Does (or why does) anyone use MapReduce anymore?
    The "streaming systems" book answers your question and more: https://www.oreilly.com/library/view/streaming-systems/9781491983867/. It gives you a history of how batch processing started with MapReduce, and how attempts at scaling by moving towards streaming systems gave us all the subsequent frameworks (Spark, Beam, etc.). As for the framework called MapReduce, it isn't used much, but its descendant... - Source: Hacker News / 4 months ago
  • How do Streaming Aggregation Pipelines work?
    Apache Beam is one of many tools that you can use. Source: 5 months ago
  • Real Time Data Infra Stack
    Apache Beam: Streaming framework which can be run on several runner such as Apache Flink and GCP Dataflow. - Source: dev.to / over 1 year ago
  • Google Cloud Reference
    Apache Beam: Batch/streaming data processing 🔗Link. - Source: dev.to / over 1 year ago
  • Composer out of resources - "INFO Task exited with return code Negsignal.SIGKILL"
    What you are looking for is Dataflow. It can be a bit tricky to wrap your head around at first, but I highly suggest leaning into this technology for most of your data engineering needs. It's based on the open source Apache Beam framework that originated at Google. We use an internal version of this system at Google for virtually all of our pipeline tasks, from a few GB, to Exabyte scale systems -- it can do it all. Source: over 1 year ago
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What are some alternatives?

When comparing Talend Big Data Platform and Apache Beam, you can also consider the following products

Talend Data Integration - Talend offers open source middleware solutions that address big data integration, data management and application integration needs for businesses of all sizes.

Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.

Matillion - Matillion is a cloud-based data integration software.

Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.

Talend Data Services Platform - Talend Data Services Platform is a single solution for data and application integration to deliver projects faster at a lower cost.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.