Remove apache-kafka-vs-confluent
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Analysis of Confluent Buying Immerok

Jesse Anderson

If you haven’t heard, Confluent announced they’re buying Immerok. This purchase represents a significant shift in strategy for Confluent. I’ve always been vocal about ksqlDB’s and Kafka Stream’s limitations. I think this factors into Confluent’s strategy, which I’ll discuss later. In 2019, Alibaba bought Ververica.

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8 Data Ingestion Tools (Quick Reference Guide)

Monte Carlo

Batch vs. Streaming Assess if your data processing leans towards real-time analytics or if batch processing suffices for your use case. Batch vs Streaming : They focus on automated batch data integration but also support near real-time data replication for certain sources. Cost : It’s open-source software, so free.

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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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Data Engineering in Retrospect: Key Trends and Patterns of 2023

Data Engineering Weekly

We saw back-to-back articles comparing the features and the performance of Delta Lake, Apache Hudi, and Iceberg. The companies backing Apache Hudi and Iceberg write articles about comparative ACID support in both the platforms here and here. It is Databricks vs. Snowflake, where both companies ran their data conference on the same day.

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Confluent’s Data Streaming Platform Can Save Over $2.5M vs. Self-Managing Apache Kafka

Confluent

If you’re reading this, it’s likely because you are leveraging (or considering) Apache Kafka® in your organization—especially as it has become the de facto standard for data streaming. Adopted by […].

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Change Data Capture For All Of Your Databases With Debezium

Data Engineering Podcast

How has the tight coupling with Kafka impacted the direction and capabilities of Debezium? What are some of the design tensions that exist in the Debezium community between acting as a simple pipe vs. adding functionality for interpreting/aggregating/formatting the information contained in the changesets? Pulsar, Bookkeeper, Pravega)?

Database 100
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Rebuilding Yelp's Data Pipeline with Justin Cunningham - Episode 5

Data Engineering Podcast

As you were picking the components for your pipeline, how did you prioritize the build vs buy decisions and what are the pieces that you ended up building in-house? As you were picking the components for your pipeline, how did you prioritize the build vs buy decisions and what are the pieces that you ended up building in-house?