Amazon Redshift now supports incremental refresh on Materialized Views (MVs) for data lake tables - AWS
Amazon Redshift now supports incremental refresh of Materialized Views (MVs) on data lake tables. This capability helps customers improve query performance for their data lake queries in a cost effective and efficient manner. By enabling incremental refresh for MVs, customers can maintain up-to-date data in a more efficient and affordable way. Customers leverage data lake tables to achieve cost ef
How Notion build and grew our data lake to keep up with rapid growth
By XZ Tie, Nathan Louie, Thomas Chow, Darin Im, Abhishek Modi, Wendy Jiao In the past three years Notion’s data has expanded 10x due to user and content growth, with a doubling rate of 6-12 months. Managing this rapid growth while meeting the ever-increasing data demands of critical product and analytics use cases, especially our recent Notion AI features, meant building and scaling Notion’s data
Centrally manage access and permissions for Amazon Redshift data sharing with AWS Lake Formation | Amazon Web Services
AWS Big Data Blog Centrally manage access and permissions for Amazon Redshift data sharing with AWS Lake Formation Today’s global, data-driven organizations treat data as an asset and use it across different lines of business (LOBs) to drive timely insights and better business decisions. Amazon Redshift data sharing allows you to securely share live, transactionally consistent data in one Amazon R
Preview: Amazon Security Lake – A Purpose-Built Customer-Owned Data Lake Service | Amazon Web Services
AWS News Blog Preview: Amazon Security Lake – A Purpose-Built Customer-Owned Data Lake Service To identify potential security threats and vulnerabilities, customers should enable logging across their various resources and centralize these logs for easy access and use within analytics tools. Some of these data sources include logs from on-premises infrastructure, firewalls, and endpoint security so
Parquet and Postgres in the Data Lake | Crunchy Data Blog
Static Data is Different A couple weeks ago, I came across a blog from Retool on their experience migrating a 4TB database. They put in place some good procedures and managed a successful migration, but the whole experience was complicated by the size of the database. The size of the database was the result of a couple of very large "logging" tables: an edit log and an audit log. The thing about l
The #1 Open Source Metadata Platform | DataHub
Unified discovery, observability, and governance for data and AI. Enable everyone in your organization to effortlessly discover trustworthy data, with experiences tailored for each persona.Eliminate breaking changes with detailed cross-platform and column-level lineage. Build confidence in your data with a comprehensive view of business, operational, and technical context, all in one place. Learn
Modern Data Lakes Overview | Developer.sh | Analytics [ Consulting | System Integration | Services ]
BackgroundAs Data volumes grow to new, unprecedented levels, new tools and techniques are coming into picture to handle this growth. One of the fields that evolved is Data Lakes. In this post we'll take a look at the story of evolution of Data Lakes and how modern Data Lakes like Iceberg, Delta Lake are solving important problems. Traditionally Data Warehouse tools were used to drive business inte
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GitHub - datahub-project/datahub: The Metadata Platform for your Data and AI Stack
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