Remove create-dynamic-kafka-connect-source-connectors
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Projects in SQL Stream Builder

Cloudera

Businesses everywhere have engaged in modernization projects with the goal of making their data and application infrastructure more nimble and dynamic. Tracking changes in a project As any software project, SSB projects are constantly evolving as users create or modify resources, run queries and create jobs.

SQL 79
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New Snowflake Features Released in May–July 2023

Snowflake

At Snowflake Summit, we announced a wave of product innovations: Snowpark ML Modeling API, Snowflake Native App Framework, Dynamic Tables and more. Read our Summit recap blog for highlights across industries or watch Summit sessions now on-demand. This is where Dynamic Tables (currently in public preview) come in.

Scala 52
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Analytics on DynamoDB: Comparing Elasticsearch, Athena and Spark

Rockset

In this blog post I compare options for real-time analytics on DynamoDB - Elasticsearch , Athena, and Spark - in terms of ease of setup, maintenance, query capability, latency. We can use AWS Glue to perform the ETL process and create a complete copy of the DynamoDB table in S3.

NoSQL 52
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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 89
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Building a Scalable Search Architecture

Confluent

Luckily, this task looks a lot like the way we tackle problems that arise when connecting data. Distributed transactions are very hard to implement successfully, which is why we’ll introduce a log-inspired system such as Apache Kafka ®. Building an indexing pipeline at scale with Kafka Connect.

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Putting Events in Their Place with Dynamic Routing

Confluent

In the Apache Kafka ® world, this means that each of those microservice client applications subscribes to a common Kafka topic. Once this stream is created, the application may take any action on the events using the rich Kafka Streams API. Branching an event stream. Next, let’s modify the requirement.

Kafka 108
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Internal services pipeline in Analytics Platform

Picnic Engineering

The data is loaded into Snowflake, Picnic’s single source of truth Data Warehouse (DWH). We use the RabbitMQ Source connector for Apache Kafka Connect. Finally, the Snowflake sink connector picks the messages from topics and loads them into respective tables in DWH.

Kafka 52