Remove Data Architecture Remove Data Lake Remove Metadata
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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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Simplifying Data Architecture and Security to Accelerate Value

Snowflake

Whether it’s unifying transactional and analytical data with Hybrid Tables, improving governance for an open lakehouse with Snowflake Open Catalog or enhancing threat detection and monitoring with Snowflake Horizon Catalog , Snowflake is reducing the number of moving parts to give customers a fully managed service that just works.

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Announcing New Innovations for Data Warehouse, Data Lake, and Data Lakehouse in the Data Cloud 

Snowflake

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.

Data Lake 114
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Being Data Driven At Stripe With Trino And Iceberg

Data Engineering Podcast

In this episode Kevin Liu shares some of the interesting features that they have built by combining those technologies, as well as the challenges that they face in supporting the myriad workloads that are thrown at this layer of their data platform. Can you describe what role Trino and Iceberg play in Stripe's data architecture?

Data Lake 147
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Cloudera and Snowflake Partner to Deliver the Most Comprehensive Open Data Lakehouse

Cloudera

In August, we wrote about how in a future where distributed data architectures are inevitable, unifying and managing operational and business metadata is critical to successfully maximizing the value of data, analytics, and AI.

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Presto Powered Cloud Data Lakes At Speed Made Easy With Ahana

Data Engineering Podcast

Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. lets you identify data quality issues and their root causes from a single dashboard.

Data Lake 100
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Why Open Table Format Architecture is Essential for Modern Data Systems

phData: Data Engineering

First, we create an Iceberg table in Snowflake and then insert some data. Then, we add another column called HASHKEY , add more data, and locate the S3 file containing metadata for the iceberg table. In the screenshot below, we can see that the metadata file for the Iceberg table retains the snapshot history.