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Stream Rows and Kafka Topics Directly into Snowflake with Snowpipe Streaming

Snowflake

As part of this, we are also supporting Snowpipe Streaming as an ingestion method for our Snowflake Connector for Kafka. Now we are able to ingest our data in near real time directly from Kafka topics to a Snowflake table, drastically reducing the cost of ingestion and improving our SLA from 15 minutes to within 60 seconds.

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Creating a Data Pipeline with Spark, Google Cloud Storage and Big Query

Towards Data Science

It’s possible to go from simple ETL pipelines built with python to move data between two databases to very complex structures, using Kafka to stream real-time messages between all sorts of cloud structures to serve multiple end applications. Google Cloud Storage (GCS) is Google’s blob storage. Image by the author.

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The Rise of Managed Services for Apache Kafka

Confluent

As a distributed system for collecting, storing, and processing data at scale, Apache Kafka ® comes with its own deployment complexities. To simplify all of this, different providers have emerged to offer Apache Kafka as a managed service. Before Confluent Cloud was announced , a managed service for Apache Kafka did not exist.

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The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

Kafka can continue the list of brand names that became generic terms for the entire type of technology. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. What is Kafka?

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?? On Track with Apache Kafka – Building a Streaming ETL Solution with Rail Data

Confluent

Using this data, Apache Kafka ® and Confluent Platform can provide the foundations for both event-driven applications as well as an analytical platform. With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers. Ingesting the data.

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Deploying Kafka Streams and KSQL with Gradle – Part 3: KSQL User-Defined Functions and Kafka Streams

Confluent

As discussed in part 2, I created a GitHub repository with Docker Compose functionality for starting a Kafka and Confluent Platform environment, as well as the code samples mentioned below. gradlew ksql:pipelineExecute , we might see the following error: error_code: 40001: Kafka topic does not exist: clickstream. Kafka Streams.

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Deploying Kafka Streams and KSQL with Gradle – Part 2: Managing KSQL Implementations

Confluent

In part 1 , we discussed an event streaming architecture that we implemented for a customer using Apache Kafka ® , KSQL from Confluent, and Kafka Streams. In part 3, we’ll explore using Gradle to build and deploy KSQL user-defined functions (UDFs) and Kafka Streams microservices. gradlew composeUp. The KSQL pipeline flow.

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