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Powering Real-Time Analytics at Scale on MySQL and PostgreSQL

Rockset

Rockset replicates the data in real-time from your primary database, including both the initial full-copy data replication into Rockset and staying in sync by continuously reading your MySQL or PostgreSQL change streams.

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Easier Stream Processing On Kafka With ksqlDB

Data Engineering Podcast

The ksqlDB project was created to address this state of affairs by building a unified layer on top of the Kafka ecosystem for stream processing. Developers can work with the SQL constructs that they are familiar with while automatically getting the durability and reliability that Kafka offers. How is ksqlDB architected?

Kafka 100
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Ingest Data Faster, Easier and Cost-Effectively with New Connectors and Product Updates

Snowflake

Snowflake is launching native integrations with some of the most popular databases, including PostgreSQL and MySQL. Developers can operationalize their analytics, AI and ML workflows by bringing Postgres and MySQL data into Snowflake with lower latency.

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Kafka Connect Deep Dive – JDBC Source Connector

Confluent

One of the most common integrations that people want to do with Apache Kafka ® is getting data in from a database. The existing data in a database, and any changes to that data, can be streamed into a Kafka topic. Here, I’m going to dig into one of the options available—the JDBC connector for Kafka Connect. Introduction.

Kafka 90
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Getting Started with Cloudera Stream Processing Community Edition

Cloudera

Cloudera Stream Processing (CSP), powered by Apache Flink and Apache Kafka, provides a complete stream management and stateful processing solution. In CSP, Kafka serves as the storage streaming substrate, and Flink as the core in-stream processing engine that supports SQL and REST interfaces. Apache Kafka and SMM.

Process 90
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Reliable Data Exchange with the Outbox Pattern and Cloudera DiM

Cloudera

This external consumer can be an asynchronous process that scans the “outbox” table or the database logs for new entries, and sends the message to an event bus, such as Apache Kafka. When defining a schema for our database table, it is important to think about what fields are needed to process and route the messages to Kafka.

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Optimize Your Machine Learning Development And Serving With The Open Source Vector Database Milvus

Data Engineering Podcast

With their new managed database service you can launch a production ready MySQL, Postgres, or MongoDB cluster in minutes, with automated backups, 40 Gbps connections from your application hosts, and high throughput SSDs.