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Real-Time Sentiment Analysis with Kafka and PySpark

Towards AI

Within this article, we will explore the significance of these pipelines and utilise robust tools such as Apache Kafka and Spark to manage vast streams of data efficiently. Apache Kafka Apache Kafka is a distributed event streaming platform used for building real-time data pipelines and streaming applications.

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The winning combination for real-time insights: Messaging and event-driven architecture

IBM Journey to AI blog

However, IBM MQ and Apache Kafka can sometimes be viewed as competitors, taking each other on in terms of speed, availability, cost and skills. MQ and Apache Kafka: Teammates Simply put, they are different technologies with different strengths, albeit often perceived to be quite similar. Interested in learning more?

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Pictures and Highlights from ODSC Europe 2023

ODSC - Open Data Science

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes. Here are some highlights from ODSC Europe 2023, including some pictures of speakers and attendees, popular talks, and a summary of what kept people busy.

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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. It connects to many DBs.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes. Each node is capable of processing and storing data independently.

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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. 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. Cloud-agnostic and can run on any Kubernetes cluster. Programming language: Airflow is very versatile.