Best of Data Processing — March 2025

1. 1
   Video

   ByteByteGo·1y

   What Is the Most Popular Open-Source AI Stack?

   Open-source AI provides freedom to experiment and develop without proprietary restrictions with frameworks and tools like Next.js, Streamlit, Gradio, and FastAPI. The data layer involves retrieval-augmented generation (RAG), vector databases, and tools for diverse file formats. The back end includes FastAPI, Langchain, Metaflow, and OLama, facilitating scalable AI operations. The ecosystem also includes community-driven models from Hugging Face and dynamic LLMs like Mistral and DeepSeek.

   275
2. 2
   Article

   Tinybird·1y

   Local first.

   Tinybird introduces Tinybird Local, a Docker container that allows developers to run a full instance of Tinybird's data processing platform on their laptops. This local-first approach enables development, testing, and deployment of data applications both locally and in the cloud seamlessly. The container includes core Tinybird functionalities and several optimizations for performance but lacks some cloud-specific features. The initiative aims to provide a more controlled, offline, and versatile development environment.

   175
3. 3
   Video

   YouTube·1y

   the Spring Boot end-to-end tutorial (new for 2025!)

   Explore the essential concepts of Spring Boot 3.4 and its 2025 updates, including auto-configuration, dependency injection, and aspect-oriented programming. Learn to set up a Spring Cloud Config Server and use Spring Batch for efficient data processing. Follow along to build a dog adoption service with these tools.

   70
4. 4
   Article

   Community Picks·1y

   nuclio/nuclio: High-Performance Serverless event and data processing platform

   Nuclio is a high-performance serverless framework designed for data, I/O, and compute intensive workloads. It integrates with popular data science tools like Jupyter and Kubeflow and supports various data and streaming sources, as well as execution over CPUs and GPUs. Nuclio can be used standalone in a Docker container or on top of Kubernetes. It features rapid processing capabilities and high security, with use cases in both startups and enterprises.

   11
5. 5
   Article

   Real Python·1y

   Working With Python Polars – Real Python

   Polars is a high-performance DataFrame library for Python, designed for efficient data processing and handling large datasets. The video course introduces Polars' core features including DataFrames, expressions, contexts, reading data, grouping, aggregating, and utilizing the lazy API. The course includes 7 lessons, video subtitles, transcripts, downloadable resources, an accompanying text-based tutorial, a Q&A with Python experts, and a certificate of completion.

   10