Amazon Aurora PostgreSQL now lets you directly query Apache Iceberg and Parquet data stored in your data lake alongside live operational data—no ETL pipelines required. Powered by DuckDB embedded within Aurora, this capability enables single queries that join transactional and historical data using familiar PostgreSQL syntax. It supports AWS Glue Data Catalog, S3, and S3 Tables, with optimizations like predicate pushdown and caching for efficient performance.
Introduction In the first two parts of this series, we described how Grab approaches data mesh through the Signals Marketplace: a way for teams to publish, discover, and reuse trusted data products across domains. Part II introduced the foundational tools behind certification: Hubble for metadata and ownership, Genchi for data quality observability, and the Data Contract Registry for explicit producer-consumer guarantees. Certification is the starting point for a trusted data marketplace. It gives downstream consumers confidence in an asset’s ownership, documentation, lineage, and quality…
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MySQL/MariaDB is one of the most popular database servers and is widely used by developers worldwide to build websites, both ... Read More The post How to Install and Configure phpMyAdmin on Debian 13 appeared first on RoseHosting.
DynamoDB now supports native vector search with single-digit millisecond latency at 99%+ recall. It is designed for any scale, even trillions of vectors and requires zero infrastructure management.
Introduction: The evolution of Grab’s Data Lake At Grab’s scale, managing petabytes of data across billions of S3 objects demands more than a storage layer. It demands a robust architectural primitive that supports the high-concurrency needs of a modern “Lakehouse.” Our goal is full storage-compute separation, leveraging S3 as an elastic foundation for both near-real-time metrics and large-scale batch transformations. For years, the vast majority of our tables were Hive Parquet, managed through the Hive Metastore with a directory-based layout. This model served us well, but as data volume…
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How we made our filtering 10x cheaper by removing our Bloom FiltersBloom Filters are great tools to make fast and cheap filtering. They also come with plenty of problems and can easily get expensive and cumbersome. We switched to user-based direct database queries, which made our filtering cheaper and easy to maintain. Here’s the full breakdown of that migration.Intro: This is a 4-part series breaking down improvements to the algorithm behind the Medium’s Daily Digest over the past year. When we started this work, the Digest was suboptimal — and since it’s a huge distribution surface,…
Cross-Digest diversificationIn this part 4, we’ll see how we went from investigating a few complaints from digest power users to improving our digest recommendations across the board.Intro: This is a 4-part series breaking down improvements to the algorithm behind the Medium’s Daily Digest over the past year. When we started this work, the Digest was suboptimal — and since it’s a huge distribution surface, reaching millions of readers every day, we started working on incremental improvements.By the end of these projects, the digest was 10% more likely to convert users to paying members, less…
Discover how Bazaarvoice migrated millions of UGC records from RDS MySQL to AWS Aurora – at scale and with minimal user impact. Learn about the technical challenges, strategies, and outcomes that enabled this ambitious transformation in reliability, performance, and cost efficiency Bazaarvoice ingests and serves millions of user-generated content (UGC) items—reviews, ratings, questions, answers, and […]
Optimistic locking is a concurrency control mechanism where we assume that multiple transactions can safely access data without conflict, allowing them to proceed without locking the data upfront. Unlike pessimistic locking, where resources are locked to avoid conflicts, optimistic locking allows transactions to proceed without locks and checks for conflicts only when updating the data. If a conflict is detected (e.g., another transaction has already modified the data), the operation fails, and you can retry it.When Should You Use Optimistic Locking?Optimistic locking is ideal for use in…
This blog post explains how to create Room DAOs specifically for your Android debug build. These debug-only DAOs enable you to implement developer-centric features without affecting your production app. Keeping your codebase clean is essential for long-term maintainability. Debug-only DAOs help achieve this by isolating developer tools from user-facing features. Consider an app that caches […] The post Room Debug DAOs in Android: Streamlining Your Workflow first appeared on Blundell.
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