SQL stream processing, analytics, and management. We decouple storage and compute to offer instant failover, dynamic scaling, speedy bootstrapping, and efficient joins.
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Updated
Jul 6, 2024 - Rust
SQL stream processing, analytics, and management. We decouple storage and compute to offer instant failover, dynamic scaling, speedy bootstrapping, and efficient joins.
🏆 Spark4You Design patterns
WASP is a framework to build complex real time big data applications. It relies on a kind of Kappa/Lambda architecture mainly leveraging Kafka and Spark. If you need to ingest huge amount of heterogeneous data and analyze them through complex pipelines, this is the framework for you.
How to build a complete Data Platform -> Here
Explore real-time temperature data analysis using Apache Spark Streaming. This repository provides a sample solution for processing streaming data, performing analytics, and visualizing insights from temperature sensor data.
An open source framework for building data analytic applications.
University project for data streaming and analysis using Spotify's API
Real-time weather data pipeline using Flask, Kafka, Spark, Cassandra, and Grafana for generation, ingestion, processing, storage, and visualization respectively.
ETL With Apache Spark Deployed on K8s
Data Accelerator for Apache Spark simplifies onboarding to Streaming of Big Data. It offers a rich, easy to use experience to help with creation, editing and management of Spark jobs on Azure HDInsights or Databricks while enabling the full power of the Spark engine.
Big-Data with Apache Spark and Python.
Ophelia a PySpark analytics wrapper.
Benchmarks for data processing systems: Pathway, Spark, Flink, Kafka Streams
LiveBeats : A live dashboard for real-time music streaming insights.
Real-Time Monitor Panel for Systems Infected by a Keylogger.
Project to stream real-time orders and apply some ETL pipelines & analytics using DataBricks, Kafka, AWS
⏱ Real-Time Sentiment Analysis using PySpark and simulation of Twitter/X API using FastAPI
Enabling Continuous Data Processing with Apache Spark and Azure Event Hubs
Data Driven Sentiment Insight into Twitter(X) Trends | Kafka | Spark | Spark MLlib | Docker
Processing data streams with Kafka + Spark
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