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Comparing Tools For Data Processing Pipelines

The MLOps Blog

Typical examples include: Airbyte Talend Apache Kafka Apache Beam Apache Nifi While getting control over the process is an ideal position an organization wants to be in, the time and effort needed to build such systems are immense and frequently exceeds the license fee of a commercial offering.

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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning Blog

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. Amazon MSK makes it easy to ingest and process streaming data in real time with fully managed Apache Kafka.

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7 Best Machine Learning Workflow and Pipeline Orchestration Tools 2024

DagsHub

Thanks to its various operators, it is integrated with Python, Spark, Bash, SQL, and more. Flexibility: Its use cases are wider than just machine learning; for example, we can use it to set up ETL pipelines. Also, while it is not a streaming solution, we can still use it for such a purpose if combined with systems such as Apache Kafka.