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Apache Kafka Vs Apache Spark: Know the Differences

Knowledge Hut

A new breed of ‘Fast Dataarchitectures has evolved to be stream-oriented, where data is processed as it arrives, providing businesses with a competitive advantage. Dean Wampler (Renowned author of many big data technology-related books) Dean Wampler makes an important point in one of his webinars.

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IBM Technology Chooses Cloudera as its Preferred Partner for Addressing Real Time Data Movement Using Kafka

Cloudera

Organizations increasingly rely on streaming data sources not only to bring data into the enterprise but also to perform streaming analytics that accelerate the process of being able to get value from the data early in its lifecycle.

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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools

Monte Carlo

Key Differences Between AI Data Engineers and Traditional Data Engineers While traditional data engineers and AI data engineers have similar responsibilities, they ultimately differ in where they focus their efforts.

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How Cloudera Data Flow Enables Successful Data Mesh Architectures

Cloudera

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

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Microsoft Fabric vs. Snowflake: Key Differences You Need to Know

Edureka

Its multi-cluster shared data architecture is one of its primary features. Additionally, Fabric has deep integrations with Power BI for visualization and Microsoft Purview for governance, resulting in a smooth experience for both business users and data professionals.

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Building a Scalable Search Architecture

Confluent

Distributed transactions are very hard to implement successfully, which is why we’ll introduce a log-inspired system such as Apache Kafka ®. Building an indexing pipeline at scale with Kafka Connect. Moving data into Apache Kafka with the JDBC connector. Setting up the connector.

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Thoughts on Amazon Express One and its impact in Data Infrastructure

Data Engineering Weekly

The Current State of the Data Architecture S3 intelligent tiered storage provides a fine balance between the cost and the duration of the data retention. However, the real-time insight on accessing the recent data remains a big challenge. The combination of stream processing + OLAP storage like Pinot. What is Next?

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