--- title: Best Apache Spark posts of 2025 | daily.dev description: The most upvoted Apache Spark posts of 2025, curated by the daily.dev community. canonical: https://daily.dev/tags/spark/best-of/2025 twitter:card: summary_large_image twitter:site: @dailydotdev og:url: https://daily.dev/tags/spark/best-of/2025 og:type: website og:site_name: daily.dev og:title: Best Apache Spark posts of 2025 | daily.dev og:description: The most upvoted Apache Spark posts of 2025, curated by the daily.dev community. og:image: https://media.daily.dev/image/upload/s--VAY5ToZt--/f_auto/v1724209435/public/daily.dev%20-%20open%20graph --- # Best of Apache Spark — 2025 1. 1 [](/posts/building-a-real-time-flight-data-pipeline-with-kafka-spark-and-airflow-awklylml9 "Building a Real-Time Flight Data Pipeline with Kafka, Spark, and Airflow") Article Data Engineer Things · 1y Building a Real-Time Flight Data Pipeline with Kafka, Spark, and Airflow A comprehensive guide to building a real-time flight data pipeline using Kafka for streaming, Spark for processing, and Airflow for orchestration. The pipeline fetches live flight data from a custom API, streams it through Kafka to MongoDB for storage, then uses Airflow to schedule daily ETL jobs that extract landed flight information into PostgreSQL and generate CSV reports. The project includes Docker containerization, complete code examples, and demonstrates end-to-end data engineering practices from real-time ingestion to batch processing and reporting. 119 4 2. 2 [](/posts/end-to-end-data-engineering-system-on-real-data-with-kafka-spark-airflow-postgres-and-docker-xeryzqlco "End-to-End Data Engineering System on Real Data with Kafka, Spark, Airflow, Postgres, and Docker") Article Towards AI · 2y End-to-End Data Engineering System on Real Data with Kafka, Spark, Airflow, Postgres, and Docker The post provides a detailed guide on building an end-to-end data engineering system using Kafka for data streaming, Spark for data transformation, Airflow for orchestration, PostgreSQL for storage, and Docker for setup and deployment. It is structured into two phases: the first focuses on constructing the data pipeline, while the second will cover creating an application to interact with the database using language models. This project is particularly suited for beginners to data engineering, aiming to deepen their practical knowledge of handling data systems. 99 3. 3 [](/posts/the-new-way-to-build-pipelines-on-databricks-introducing-the-ide-for-data-engineering-qovhr2fcm "The New Way to Build Pipelines on Databricks: Introducing the IDE for Data Engineering") Article databricks · 46w The New Way to Build Pipelines on Databricks: Introducing the IDE for Data Engineering Databricks launched the IDE for Data Engineering in Public Preview, a dedicated development environment for building declarative data pipelines within the Databricks Workspace. The IDE provides an integrated experience with features like automatic dependency graph visualization, file-based dataset organization, built-in data previews, debugging tools, and Git integration. It supports the declarative programming paradigm where developers specify what they want to achieve rather than how to build it, with the editor handling execution planning and optimization. The tool consolidates pipeline authoring, testing, version control, and scheduling into a single interface, aiming to improve developer productivity and reduce context switching. 44 4. 4 [](/posts/why-i-love-python-as-data-engineer-clvvos9pf "Why I Love Python as Data Engineer") Article Data Engineer Things · 2y Why I Love Python as Data Engineer Python is favored by data engineers for its versatility, simplicity, and rich library ecosystem. It excels in both small and large-scale data tasks, making data manipulation and automation easier. Despite some limitations like slower execution speed and memory consumption, its readable code and efficient debugging make it a preferred choice for many. Python integrates well with tools like Apache Spark and libraries for data visualization, adding to its appeal. 20 [See all Apache Spark archives](/tags/spark/best-of) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@graph":[{"@type":"CollectionPage","@id":"https://daily.dev/tags/spark/best-of/2025#page","url":"https://daily.dev/tags/spark/best-of/2025","name":"Best Apache Spark Posts of 2025","description":"The most upvoted Apache Spark posts of 2025, curated by the daily.dev community.","isPartOf":{"@type":"WebSite","url":"https://daily.dev"}},{"@type":"ItemList","@id":"https://daily.dev/tags/spark/best-of/2025#items","numberOfItems":4,"itemListElement":[{"@type":"ListItem","position":1,"url":"https://daily.dev/posts/building-a-real-time-flight-data-pipeline-with-kafka-spark-and-airflow-awklylml9","name":"Building a Real-Time Flight Data Pipeline with Kafka, Spark, and Airflow"},{"@type":"ListItem","position":2,"url":"https://daily.dev/posts/end-to-end-data-engineering-system-on-real-data-with-kafka-spark-airflow-postgres-and-docker-xeryzqlco","name":"End-to-End Data Engineering System on Real Data with Kafka, Spark, Airflow, Postgres, and Docker"},{"@type":"ListItem","position":3,"url":"https://daily.dev/posts/the-new-way-to-build-pipelines-on-databricks-introducing-the-ide-for-data-engineering-qovhr2fcm","name":"The New Way to Build Pipelines on Databricks: Introducing the IDE for Data Engineering"},{"@type":"ListItem","position":4,"url":"https://daily.dev/posts/why-i-love-python-as-data-engineer-clvvos9pf","name":"Why I Love Python as Data Engineer"}]},{"@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https://daily.dev"},{"@type":"ListItem","position":2,"name":"Tags","item":"https://daily.dev/tags"},{"@type":"ListItem","position":3,"name":"Apache Spark","item":"https://daily.dev/tags/spark"},{"@type":"ListItem","position":4,"name":"Best of","item":"https://daily.dev/tags/spark/best-of"},{"@type":"ListItem","position":5,"name":"2025"}]}]} ```