Microsoft Fabric and OneLake Azure Lakehouse vs Databricks and Snowflake Cloud
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What is Microsoft Fabric for Azure Cloud (Beyond the Buzz) and how it Competes with Snowflake and Databricks

If you ask your favorite large language model, Microsoft Fabric appears to be the ultimate solution for any data challenge you can imagine. That’s also the impression many people get from Microsoft’s sales teams. But is it really the silver bullet it’s made out to be? This article takes a closer look exploring the glossy marketing and sales definition of the platform and then deconstructing it from a more practical perspective. Learn what Microsoft Fabric is truly built for, and how it fits into the wider data landscape, especially in comparison to other major players in the data analytics market like Databricks and Snowflake.
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Apache Kafka Deployment Options - Serverless vs Self-Managed vs BYOC Bring Your Own Cloud
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Deployment Options for Apache Kafka: Self-Managed, Fully-Managed / Serverless and BYOC (Bring Your Own Cloud)

BYOC (Bring Your Own Cloud) is an emerging deployment model for organizations looking to maintain greater control over their cloud environments. Unlike traditional SaaS models, BYOC allows businesses to host applications within their own VPCs to provide enhanced data privacy, security, and compliance. This approach leverages existing cloud infrastructure. It offers more flexibility for custom configurations, particularly for companies with stringent security needs. In the data streaming sector around Apache Kafka, BYOC is changing how platforms are deployed. Organizations get more control and adaptability for various use cases. But it is clearly NOT the right choice for everyone!
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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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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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Snowflake with Apache Kafka and Iceberg Connector
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Snowflake Data Integration Options for Apache Kafka (including Iceberg)

The integration between Apache Kafka and Snowflake is often cumbersome. Options include near real-time ingestion with a Kafka Connect connector, batch ingestion from large files, or leveraging a standard table format like Apache Iceberg. This blog post explores the alternatives and discusses its trade-offs. The end shows how data streaming helps with hybrid architectures where data needs to be ingested from the private data center into Snowflake in the public cloud.
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Is Amazon MSK Serverless for Apache Kafka a Self-Driving Car or just a Car Engine
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When NOT to choose Amazon MSK Serverless for Apache Kafka?

Apache Kafka became the de facto standard for data streaming. Various cloud offerings emerged and improved in the last years. Amazon MSK Serverless is the latest Kafka product from AWS. This blog post looks at its capabilities to explore how it relates to “the normal” partially managed Amazon MSK, when the serverless version is a good choice, and when other fully-managed cloud services like Confluent Cloud are the better option.
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How to choose the right Apache Kafka Offering - Confluent Cloudera Red Hat IBM Amazon AWS MSK
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Comparison of Open Source Apache Kafka vs Vendors including Confluent, Cloudera, Red Hat, Amazon MSK

Apache Kafka became the de facto standard for event streaming. Various vendors added Kafka and related tooling to their offerings or provide a Kafka cloud service. This blog post uses the car analogy – from the motor engine to the self-driving car – to explore the different Kafka offerings available on the market. The goal is not a feature-by-feature comparison. Instead, the intention is to educate about the different deployment models, product strategies, and trade-offs from the available options.
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