If you inherited an OpenSearch deployment and you're now being asked to run agents on it, Q1 2026 has been unusually good news. OpenSearch 3.5 (February) and 3.6 (April) aren't incremental search improvements — they're a clear declaration of intent. "OpenSearch isn't trying to be a better Elasticsearch; it is focused on being the data layer on which AI applications are built." That's from the arti
SQL is widely known for data querying and manipulation but systems do grow; data becomes larger; processes become repetitive and operations become sensitive. SQL has some features which enables it to be considered a fully fledged programming language. Some of the features which I discuss in this article are procedures, functions and transactions. Each of these concepts serve distinct purposes. Sto
At 100 million 768-dimensional embeddings, the gap between top-tier vector search tools isn't just measurable—it's existential. In our 6-month benchmark across 12 hardware configurations, FAISS 1.9 delivered 4.2x lower p99 latency than Chroma 0.6, while Pinecone 1.6 cost 11x more than self-hosted FAISS for equivalent throughput. Here's what the numbers actually say. What Chromium versions are ma
Hi 👋, In this post we shall explore Bedrock's structured KB with this architecture: Upload CSVs to S3 > SNS Queue > Crawl data with Glue > Query with Redshift > Bedrock KB > Query with LLM. Let's do some of this with code. Let's get started. Clone the repo and switch to the project directory. git clone [email protected]:networkandcode/networkandcode.github.io.git cd structured-kb-demo/ Do a uv sync
Subqueries vs. CTEs in SQL: A Practical Guide to Writing Cleaner, Smarter Queries Whether you're just getting comfortable with SQL or leveling up your data skills, two tools will come up again and again when working with complex queries: subqueries and Common Table Expressions (CTEs). They solve similar problems — breaking a complex query into manageable pieces — but they do it in different ways
In a previous post, I explored Codd's connection trap in PostgreSQL and MongoDB — the classic pitfall where joining two independent many-to-many relationships through a shared attribute produces spurious combinations that look like facts but aren't. The example followed Codd's 1970 suppliers–parts–projects model: we know which suppliers supply which parts, and which projects use which parts, but j
Automating Hermitage to see how transactions differ in MySQL and MariaDB
Barman – Backup and Recovery Manager for PostgreSQL