Browsing Tag

comparison

7 posts
Serverless Data Streaming on Azure Cloud with Apache Kafka Event Hubs Confluent Cloud for OneLake and Microsoft Fabric
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  • 2.0K views
  • 9 minute read

When to Choose Apache Kafka vs. Azure Event Hubs vs. Confluent Cloud for a Microsoft Fabric Lakehouse

Choosing between Apache Kafka, Azure Event Hubs, and Confluent Cloud for data streaming is critical when building a Microsoft Fabric Lakehouse. Each option caters to different needs, and this blog post will guide you in selecting the right data streaming solution for your use case.
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Apache Iceberg Open Table Format for Data Lake Lakehouse Streaming wtih Kafka Flink Databricks Snowflake AWS GCP Azure
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  • 9.6K views
  • 11 minute read

Apache Iceberg – The Open Table Format for Lakehouse AND Data Streaming

An open table format framework like Apache Iceberg is essential in the enterprise architecture to ensure reliable data management and sharing, seamless schema evolution, efficient handling of large-scale datasets and cost-efficient storage. This blog post explores market trends, adoption of table format frameworks like Iceberg, Hudi, Paimon, Delta Lake and XTable, and the product strategy of leading vendors of data platforms such as Snowflake, Databricks (Apache Spark), Confluent (Apache Kafka / Flink), Amazon Athena and Google BigQuery.
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How I Trained a Chatbot K.AI of Myself Without Coding Evaluating OpenAI Custom GPT Chatbase Botsonic LiveChatAI
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  • 2.9K views
  • 13 minute read

Hello, K.AI – How I Trained a Chatbot of Myself Without Coding Evaluating OpenAI Custom GPT, Chatbase, Botsonic, LiveChatAI

Generative AI (GenAI) enables many new use cases for enterprises and private citizens. While I work on real-time enterprise scale AI/ML deployments with data streaming, big data analytics and cloud-native software applications in my daily business life, I also wanted to train a conversational chatbot for myself. This blog post introduces my journey without coding to train K.AI, a personal chatbot that can be used to learn in a conversational pace format about data streaming and the most successful use cases in this area. Yes, this is also based on my expertise, domain knowledge and opinion, which is available as  public internet data, like my hundreds of blog articles, LinkedIn shares, and YouTube videos.
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Data Streaming Landscape 2024 around Kafka Flink and Cloud
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  • 9.9K views
  • 21 minute read

The Data Streaming Landscape 2024

The research company Forrester defines data streaming platforms as a new software category in a new Forrester Wave. Apache Kafka is the de facto standard used by over 100,000 organizations. Plenty of vendors offer Kafka platforms and cloud services. Many complementary open source stream processing frameworks like Apache Flink and related cloud offerings emerged. And competitive technologies like Pulsar, Redpanda, or WarpStream try to get market share leveraging the Kafka protocol. This blog post explores the data streaming landscape of 2024 to summarize existing solutions and market trends. The end of the article gives an outlook to potential new entrants in 2025.
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JMS Message Queue vs Apache Kafka Comparison
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  • 13.3K views
  • 19 minute read

Comparison: JMS Message Queue vs. Apache Kafka

Comparing JMS-based message queue (MQ) infrastructures and Apache Kafka-based data streaming is a widespread topic. Unfortunately, the battle is an apple-to-orange comparison that often includes misinformation and FUD from vendors. This blog post explores the differences, trade-offs, and architectures of JMS message brokers and Kafka deployments. Learn how to choose between JMS brokers like IBM MQ or RabbitMQ and open-source Kafka or serverless cloud services like Confluent Cloud.
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The Trinity of Data Streaming in Industrial IoT - Apache Kafka MQTT OPC UA
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  • 11.2K views
  • 15 minute read

OPC UA, MQTT, and Apache Kafka – The Trinity of Data Streaming in IoT

In the IoT world, MQTT and OPC UA have established themselves as open and platform-independent standards for data exchange in Industrial IoT and Industry 4.0 use cases. Data Streaming with Apache Kafka is the data hub for integrating and processing massive volumes of data at any scale in real-time. This blog post explores the relationship between Kafka and the IoT protocols, when to use which technology, and why sometimes HTTP/REST is the better choice. The end explores real-world case studies from Audi and BMW.
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