Remove kafka-connect-improvements-in-apache-kafka-2-3
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Druid Deprecation and ClickHouse Adoption at Lyft

Lyft Engineering

Introduction At Lyft, we have used systems like Apache ClickHouse and Apache Druid for near real-time and sub-second analytics. In this particular blog post, we explain how Druid has been used at Lyft and what led us to adopt ClickHouse for our sub-second analytic system. ioConfig: Kafka server info, topic names, etc.

Kafka 104
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Upgrade Journey: The Path from CDH to CDP Private Cloud

Cloudera

The customer also wanted to utilize the new features in CDP PvC Base like Apache Ranger for dynamic policies, Apache Atlas for lineage, comprehensive Kafka streaming services and Hive 3 features that are not available in legacy CDH versions. ACID transactions, ANSI 2016 SQL SupportMajor Performance improvements.

Cloud 131
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A Reference Architecture for the Cloudera Private Cloud Base Data Platform

Cloudera

This blog post provides an overview of best practice for the design and deployment of clusters incorporating hardware and operating system configuration, along with guidance for networking and security as well as integration with existing enterprise infrastructure. Introduction and Rationale. Further information and documentation [link] .

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Introducing Cloudera DataFlow Designer: Self-service, No-Code Dataflow Design

Cloudera

Cloudera has been providing enterprise support for Apache NiFi since 2015, helping hundreds of organizations take control of their data movement pipelines on premises and in the public cloud. Now, we shift focus on the needs of developers and addressing the challenges they face when building dataflows in the cloud.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

This blog will give you an in-depth knowledge of what is a data pipeline and also explore other aspects such as data pipeline architecture, data pipeline tools, use cases, and so much more. It can also consist of simple or advanced processes like ETL (Extract, Transform and Load) or handle training datasets in machine learning applications.

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Deployment of Exabyte-Backed Big Data Components

LinkedIn Engineering

Co-authors: Arjun Mohnot , Jenchang Ho , Anthony Quigley , Xing Lin , Anil Alluri , Michael Kuchenbecker LinkedIn operates one of the world’s largest Apache Hadoop big data clusters. Scalability was a significant concern, as using SSH for multiple connections simultaneously caused delays, timeouts, and reduced availability.

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Delta: A Data Synchronization and Enrichment Platform

Netflix Tech

Another issue exists for the capture of schema changes, where some systems, like MySQL, don’t support transactional schema changes [1][2]. Thus, ensuring the atomicity of writes across different storage technologies remains a challenging problem for applications [3]. Now the challenge becomes how to keep these datastores in sync.