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Kai Waehner
Global Field CTO | Author | International Speaker | Follow me with Data in Motion
Kai Waehner is the Global Field CTO at Confluent, a company focused on Apache Kafka and data streaming technologies.13 He works with customers, prospects, and partners worldwide, spanning the US, EMEA, and APAC regions.1 Kai is a prominent figure in application integration and big data analytics, regularly speaking at international conferences like Devoxx, Kafka Summit, and O'Reilly Software Architecture.2
As a Field CTO, Kai's responsibilities include:
- Interacting with senior executives and technical experts in Fortune and Global 2000 companies2
- Explaining strategic and tactical concepts to customers2
- Serving as an intermediary between customers and product management2
- Staying up-to-date on industry trends to act as a thought leader and trusted advisor2
- Sharing expertise in technologies like event streaming, middleware, databases, big data, machine learning, and IoT2
Kai is also an author and international speaker, frequently writing articles and blog posts about modern enterprise architectures and innovative open-source and cloud technologies.1 His LinkedIn username is kaiwaehner.1
Highlights
#Confluent + #WarpStream = Large-Scale Streaming in your #Cloud => Confluent acquires WarpStream (= #ApacheKafka as #BYOC, Bring-your-Own-Cloud) to provide a third deployment option besides self-managed and serverless #datastreaming for strict cloud-native security requirements.
Read all the details in Jay Kreps's announcement: https://lnkd.in/eP3cZugn
"Snowflake Data Integration Options for Apache Kafka (including Iceberg)" => Store data once, consume from anywhere (Snowflake, Databricks, Apache Flink, etc.)
The integration between #ApacheKafka and #Snowflake is often cumbersome. Options include near real-time ingestion with a #KafkaConnect connector, batch ingestion from large files, or leveraging a standard table format like #ApacheIceberg.
This blog post explores the alternatives and discusses its trade-offs. The end shows how #datastreaming helps with hybrid architectures where data needs to be ingested from the private data center into Snowflake in the public cloud.
https://lnkd.in/eDcJbpcT
