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How Apache Iceberg Is Changing the Face of Data Lakes

Snowflake

Data storage has been evolving, from databases to data warehouses and expansive data lakes, with each architecture responding to different business and data needs. Traditional databases excelled at structured data and transactional workloads but struggled with performance at scale as data volumes grew.

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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

The world we live in today presents larger datasets, more complex data, and diverse needs, all of which call for efficient, scalable data systems. Though basic and easy to use, traditional table storage formats struggle to keep up. Track data files within the table along with their column statistics. Contact phData Today!

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CockroachDB In Depth with Peter Mattis - Episode 35

Data Engineering Podcast

Summary With the increased ease of gaining access to servers in data centers across the world has come the need for supporting globally distributed data storage. With the first wave of cloud era databases the ability to replicate information geographically came at the expense of transactions and familiar query languages.

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Reflections On Designing A Data Platform From Scratch

Data Engineering Podcast

If you’re a data engineering podcast listener, you get credits worth $3000 on an annual subscription TimescaleDB, from your friends at Timescale, is the leading open-source relational database with support for time-series data. Time-series data is time stamped so you can measure how a system is changing.

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AWS Shared Responsibility Model – Amazon Web Services

Edureka

Similarly, Amazon Relational Database Service (RDS) handles database engine patching, OS hardening, and underlying storage durability, while customers configure database users, schemas, and encryption settings. AWS manages the underlying infrastructure, OS, and runtime components.

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Data Engineering Weekly #175

Data Engineering Weekly

link] Open AI: Model Spec LLM models are slowly emerging as the intelligent data storage layer. Similar to how data modeling techniques emerged during the burst of relation databases, we started to see similar strategies for fine-tuning and prompt templates. Will they co-exist or fight with each other?

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Hadoop vs Spark: Main Big Data Tools Explained

AltexSoft

Master Nodes control and coordinate two key functions of Hadoop: data storage and parallel processing of data. Worker or Slave Nodes are the majority of nodes used to store data and run computations according to instructions from a master node. Data storage options. Data management and monitoring options.