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Beyond Kafka: Conversation with Jark Wu on Fluss - Streaming Storage for Real-Time Analytics

Data Engineering Weekly

I spoke with Jark Wu , who leads the Fluss and Flink SQL team at Alibaba Cloud, to understand its origins and potential. It addresses many of Kafka's challenges in analytical infrastructure. The combination of Kafka and Flink is not a perfect fit for real-time analytics; the integration of Kafka and Lakehouse is very shallow.

Kafka 73
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StreamNative Brings Streaming Data To The Cloud Native Landscape With Pulsar

Data Engineering Podcast

His most recent endeavor at StreamNative is focused on combining the capabilities of Pulsar with the cloud native movement to make it easier to build and scale real time messaging systems with built in event processing capabilities. How have projects such as Kafka and Pulsar impacted the broader software and data landscape?

Cloud 100
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Aggregator Leaf Tailer: An Alternative to Lambda Architecture for Real-Time Analytics

Rockset

That also meant a system that took full advantage of cloud efficiencies –responsive resource scheduling and disaggregation of compute and storage–while abstracting away all infrastructure-related details from users. This architecture has become popular in the last decade because it addresses the stale-output problem of MapReduce systems.

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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Ascend users love its declarative pipelines, powerful SDK, elegant UI, and extensible plug-in architecture, as well as its support for Python, SQL, Scala, and Java. In fact, while only 3.5%

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An Overview of Real Time Data Warehousing on Cloudera

Cloudera

Data streamed in is queryable in conjunction with historical data, avoiding need for Lambda Architecture. Figure 1 below shows a standard architecture for a Real-Time Data Warehouse. Cloudera offers a platform, Cloudera Data Platform (CDP), for building end-to-end data applications in both the public and private cloud.

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What is Data Ingestion? Types, Frameworks, Tools, Use Cases

Knowledge Hut

Lambda architecture: A combination of both batch and real-time processing, the lambda architecture has three layers. The lambda architecture ensures completeness of data with minimal latency. This API acts as a proxy between the application and the cloud services ensuring seamless transfer of data.

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Data Engineering Weekly #138

Data Engineering Weekly

Architectural patterns like Lambda Architecture and Kappa Architecture emerged to bridge the gap between real-time and batch data processing. Each architectural pattern has its limitation. link] Grab: Zero traffic cost for Kafka consumers. This opens the door to a more cost-efficient design.