Can Apache Kafka Replace a Database? – The 2020 Update
Kai Waehner
Can and should Apache Kafka replace a database? How long can and should I store data in Kafka?…
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Analytics
37 posts
Streaming Machine Learning with Apache Kafka, Tiered Storage, TensorFlow
The combination of streaming machine learning (ML), Apache Kafka and Confluent Tiered Storage enables you to build one…
Apache Kafka is the New Black at the Edge in Industrial IoT, Logistics and Retailing
The following question comes up almost every week in conversations with customers: Can and should I deploy Apache…
Apache Kafka as Digital Twin for Open, Scalable, Reliable Industrial IoT (IIoT)
This blog post discusses the benefits of a Digital Twin in Industrial IoT (IIoT) and its relation to…
Apache Kafka in the Automotive Industry
In November 2019, I had the pleasure to visit “Motor City” Detroit. I met with several automotive companies,…
IoT Live Demo – 100.000 Connected Cars with Kubernetes, Kafka, MQTT, TensorFlow
Live Demo – 100.000 Connected Cars – Real Time Processing and Analytics with Kubernetes, Kafka, MQTT and TensorFlow leveraging Confluent and HiveMQ.
Apache Kafka, KSQL and Apache PLC4X for IIoT Data Integration and Processing
Data integration and processing in Industrial IoT (IIoT, aka Industry 4.0 or Automation Industry). Apache Kafka, its ecosystem (Kafka Connect, KSQL) and Apache PLC4X are a great open source choice to implement this integration end to end in a scalable, reliable and flexible way.
Apache Kafka and Machine Learning for Real Time Supply Chain Optimization in IIoT
Apache Kafka and Machine Learning for Real Time Supply Chain Optimization: Integrate in real time with the legacy world and proprietary IIoT protocols (like Siemens S7, Modbus, Beckhoff ADS, OPC-UA, et al). You can process the data at scale and then ingest it into a modern database or analytic / machine learning framework.
Apache Kafka + KSQL + TensorFlow for Data Scientists via Python + Jupyter Notebook
Streaming Processing with Apache Kafka and KSQL for Data Scientists via Python and Jupyter Notebooks to build analytic models with TensorFlow and Keras.
Deep Learning KSQL UDF for Streaming Anomaly Detection of MQTT IoT Sensor Data
KSQL UDF for sensor analytics. Leverages the new API features of KSQL to build UDF / UDAF functions easily with Java to do continuous stream processing with Apache Kafka. Use Case: Connected Cars – Real Time Streaming Analytics using Deep Learning.
