Remove Kafka Remove Lambda Architecture Remove SQL
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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. Jark is a key figure in the Apache Flink community, known for his work in building Flink SQL from the ground up and creating Flink CDC and Fluss. It addresses many of Kafka's challenges in analytical infrastructure.

Kafka 74
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8 Essential Data Pipeline Design Patterns You Should Know

Monte Carlo

Lambda Architecture Pattern 4. Kappa Architecture Pattern 5. Lambda Architecture Pattern Here’s where things get interesting. Lambda architecture is like having both a regular washing machine for your weekly loads AND that magical instant-wash machine. Batch Processing Pattern 2.

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

Rockset

That meant a system that was sufficiently nimble and powerful to execute fast SQL queries on raw data, essentially performing any needed transformations as part of the query step, and not as part of a complex data pipeline. A common implementation would have large batch jobs in Hadoop complemented by an update stream stored in Apache Kafka.

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Building A Data Lake For The Database Administrator At Upsolver

Data Engineering Podcast

In order to bring the DBA into the new era of data management the team at Upsolver added a SQL interface to their data lake platform. How does the introduction of a universal SQL layer change the staffing requirements for building and maintaining a data lake? How is the SQL layer in Upsolver implemented?

Data Lake 100
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An Exploration Of The Expectations, Ecosystem, and Realities Of Real-Time Data Applications

Data Engineering Podcast

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. 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.

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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. SQL editor for running Hive and Impala queries. SQL editor for running Impala+Kudu queries. with low latency and high concurrency.

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Data Engineering Weekly #138

Data Engineering Weekly

Data Engineering Weekly Is Brought to You by RudderStack RudderStack Profiles takes the SaaS guesswork, and SQL grunt work out of building complete customer profiles, so you can quickly ship actionable, enriched data to every downstream team. Each architectural pattern has its limitation. Write SQL queries without learning SQL?