Real Time Analytics
Showing 36 of 69 projects
A Python ETL framework for stream processing, real-time analytics, and building live LLM/RAG pipelines, powered by a scalable Rust engine.
A distributed event streaming platform for building high-performance data pipelines, streaming analytics, and data integration.
A scalable time series database optimized for real-time metrics, events, and analytics with fast query response.
A scalable time series database optimized for real-time metrics, events, and analytics with fast query response.
A real-time web log analyzer and interactive viewer that runs in terminal or browser for instant server monitoring.
An open-source time-series database for high-speed ingestion and low-latency SQL queries.
A high-performance real-time analytics database designed for fast queries and ingest to reduce time to insight.
A PostgreSQL extension that transforms Postgres into a distributed database for high performance at any scale.
An enterprise-grade event streaming platform that ingests, processes, and manages real-time event data with PostgreSQL compatibility and Apache Iceberg™ integration.
Enterprise-grade event streaming platform that continuously ingests, processes, and serves real-time data with Apache Iceberg™ integration.
High-performance messaging system for reliable UDP unicast, UDP multicast, and IPC transport with predictable low latency.
A real-time terminal monitoring tool for Claude AI token usage with ML-based predictions, cost analysis, and a Rich UI.
A web-based network traffic monitoring and security analysis application for real-time network visibility.
Open-source customer data infrastructure that collects, validates, and enriches behavioral event data for AI and analytics.
A distributed stream processing engine in Rust that performs stateful computations on real-time data with subsecond results.
Apache Heron is a real-time, distributed, fault-tolerant stream processing engine developed by Twitter.
A curated list of awesome streaming frameworks, applications, readings, and resources for stream processing.
A Kubernetes-native, serverless platform for running massively parallel data and streaming jobs with exactly-once semantics.
A single C++ binary SQL engine for high-performance stream processing, analytics, observability, and AI/ML pipelines.
A masterless, cloud-scale, fault-tolerant distributed computation system for batch and stream processing written in Clojure.
Native integration library for using Elasticsearch with Hadoop, Spark, and Hive for real-time search and analytics on big data.
A fast, modern, cookie-free analytics tool that can be self-hosted or used via cloud, providing AI-powered dashboards with setup in under 30 seconds.
A cloud-native streaming and complex event processing engine that executes Streaming SQL queries for real-time event processing.
A Python framework for building real-time data pipelines and event-driven microservices on Apache Kafka using a Streaming DataFrame API.
A high-performance Rust stream processing engine with integrated AI capabilities for real-time data processing and intelligent analysis.
An open-source, in-memory, distributed batch and stream processing engine for Java applications.
A Java/.NET component for complex event processing (CEP), streaming SQL, and event series analysis.
A distributed stream processing framework built on Apache Kafka and Apache Hadoop YARN for fault-tolerant, stateful processing.
A low-code visual tool for domain experts to build, run, and monitor real-time decision algorithms on streaming data.
A universal HTAP engine providing ACID transactions and real-time analytics across diverse databases.
Real-time .NET error reporting clients for ASP.NET, Web API, WPF, Console, and MVC applications.
An ultra-fast .NET library for complex event processing and time series manipulation, handling historical and real-time data streams.
A real-time online machine learning library built on Apache Storm for scalable stream processing with incremental algorithms.
A unified platform for big data stream and batch processing on Hadoop YARN with enterprise-grade operability.
A Java library for building data pipelines that connect Amazon Kinesis streams to AWS and non-AWS services like DynamoDB, Redshift, S3, and Elasticsearch.
A distributed, scalable database built for stream processing applications on Apache Kafka using SQL syntax.
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