Azure Event Hubs VS Apache Kafka

Azure Event Hubs Reviews

Apache Kafka Reviews

Azure Event Hubs mentions (4)

• Anyone routing firewall logs to Microsoft Event Hubs?

  We're looking into some sort of cloud-based solution to route our Palo Alto firewall logs to across our customer base. I'm with an MSP that manages over a hundred PA firewalls. I was intrigued by the Event Hubs (https://azure.microsoft.com/en-us/products/event-hubs/) solution as a way to push logs to it and then ingest them from there into our SIEM, without having to deal with challenges of multi-tenancy and... Source: over 1 year ago

• Microsoft Releases Stream Analytics No-Code Editor into General Availability

  Microsoft released Azure Stream Analytics no-code editor, a drag-and-drop canvas for developing jobs for stream processing scenarios such as streaming ETL, ingestion, and materializing data to data into general availability. The no-code editor is hosted in the company’s big-data streaming platform and event ingestion service, Azure Event Hubs. Interestingly, the offering follows up after Confluent's recent release... Source: over 1 year ago

• Infrastructure as code (IaC) for Java-based apps on Azure

  Sometimes you don’t need an entire Java-based microservice. You can build serverless APIs with the help of Azure Functions. For example, Azure functions have a bunch of built-in connectors like Azure Event Hubs to process event-driven Java code and send the data to Azure Cosmos DB in real-time. FedEx and UBS projects are great examples of real-time, event-driven Java. I also recommend you to go through 👉 Code,... - Source: dev.to / over 1 year ago

• Setting up demos in Azure - Part 1: ARM templates

  For event infrastructure, we have a bunch of options, like Azure Service Bus, Azure Event Grid and Azure Event Hubs. Like the databases, they aren't mutually exclusive and I could use all, depending on the circumstance, but to keep things simple, I'll pick one and move on. Right now I'm more inclined towards Event Hubs, as it works similarly to Apache Kafka, which is a good fit for the presentation context. - Source: dev.to / about 3 years ago

Apache Kafka mentions (120)

• Empowering Real-Time Data Pipelines: Leveraging Apache Kafka and Rudderstack

  In today’s fast-paced digital landscape, effective data management and analysis are essential for businesses aiming to stay ahead of the curve. Fortunately, modern tools like Apache Kafka and RudderStack have revolutionized the way we handle and derive insights from large datasets. In this blog post, we’ll explore our experience implementing the Kafka Sink Connector to facilitate seamless event data transfer to... - Source: dev.to / about 1 month ago

• Choosing Between a Streaming Database and a Stream Processing Framework in Python

  Stream-processing platforms such as Apache Kafka, Apache Pulsar, or Redpanda are specifically engineered to foster event-driven communication in a distributed system and they can be a great choice for developing loosely coupled applications. Stream processing platforms analyze data in motion, offering near-zero latency advantages. For example, consider an alert system for monitoring factory equipment. If a... - Source: dev.to / 2 months ago

• How to Use Reductstore as a Data Sink for Kafka

  Apache Kafka is a distributed streaming platform capable of handling high throughput of data, while ReductStore is a databases for unstructured data optimized for storing and querying along time. - Source: dev.to / 3 months ago

• 🦿🛴Smarcity garbage reporting automation w/ ollama

  *Push data *(original source image, GPS, timestamp) in a common place (Apache Kafka,...). - Source: dev.to / 3 months ago

• How to Build & Deploy Scalable Microservices with NodeJS, TypeScript and Docker || A Comprehesive Guide

  RabbitMQ comes with administrative tools to manage user permissions and broker security and is perfect for low latency message delivery and complex routing. In comparison, Apache Kafka architecture provides secure event streams with Transport Layer Security(TLS) and is best suited for big data use cases requiring the best throughput. - Source: dev.to / 3 months ago