NebulaGraph has no unique indexes, so duplicates in a graph load usually come from unstable vertex IDs and edge ranks. The author shows how to derive deterministic VIDs from business keys with FNV-1a and pin edge rank, which makes repeated loads safe. A batched .NET ingestion pipeline with checkpoints and retries is included.
Azure SQL Database Hyperscale splits a single-writer SQL engine across separate compute, log, page server and storage tiers, so it is distributed in architecture but not in write capacity. The author explains where that line falls against the usual meaning of distributed SQL, and cites a commissioned benchmark against Aurora PostgreSQL. Useful when you choose a database for a growing workload.
In SQL Server 2019 and later, varchar columns using a collation whose name ends in _UTF8 can store Unicode text, so not every text column has to become nvarchar. The change is more than a single database setting, though: comparisons, sorting, unique indexes and storage sizes all shift. The article lays out a step-by-step path from column inventory to production rollout.
This post explains how a .NET ERP framework applies TableSchema definitions to the physical database without migration scripts. Each upgrade compares the live structure with the definition, then separates compare, plan and execute so the mode (ALTER or rebuild) can be checked before running. It is useful for developers who maintain schemas that already hold production data.
CodoMetis.ValueRanges 10.4 and EFCore.ComplexIndexes are used to build a holiday-cottage booking API end to end. Date ranges are modelled as single values, overlapping bookings are blocked by a PostgreSQL exclusion constraint, and free nights are computed in one query. A practical example for EF Core developers working with PostgreSQL.
Microsoft Fabric's Materialized Lake Views persist Lakehouse transformations as Delta tables, letting Fabric decide how each view refreshes and enforcing data quality constraints along the way. The article walks through how MLVs fit Bronze, Silver and Gold layers, which refresh strategies apply, and where they fall short. Read it if your Fabric pipelines are stitched together from notebooks and orchestration jobs.
This article outlines five EF Core query patterns behind many slow pages, plus one habit that catches them all: read the SQL EF generates instead of judging the C# code. It covers N+1 queries, loading whole tables or unneeded columns, cartesian explosions from collection Includes, and filters that prevent index use. It is a practical checklist for anyone writing data access code.
Jeremy D. Miller strongly recommends that Event Sourcing developers model domain logic with the Decider pattern instead of the older AggregateRoot pattern. He explains why pure decide functions in Marten and Wolverine handlers are easier to reason about, test and debug. The post is a useful reference for anyone choosing a design for event-sourced .NET systems.
The Azure Cosmos DB Change Feed Processor spreads change processing across several .NET workers using a lease container for ownership and checkpoints. The article walks through the setup in the .NET SDK and explains when adding workers actually helps. It also covers why downstream operations must be idempotent, since changes can be delivered again after a failure.
ServiceStack v10.4 adds db.Explain() to OrmLite, which returns the query plan of a typed query without running it. The Profiling Admin UI also gets a Slowest Queries view where you can explain, analyze and re-run an app's slowest SQL from the browser. Together they make it easier to spot missing indexes.
Microsoft Fabric IQ is a new Fabric workload that maps OneLake tables, Power BI semantic models and real-time Eventhouse streams to shared business entities. Its Ontology item, currently in preview, lets Fabric Data Agents and Operations Agents work with business concepts instead of raw schemas. Read on if you are deciding whether to model business meaning before connecting LLMs to your data.
This installment of Microsoft's PostgreSQL-to-SQL field notes compares how each engine helps you diagnose slow queries. It shows which Azure SQL dynamic management views and functions expose in-flight plans, last actual plans, wait statistics and memory grants without preinstalled extensions. Developers moving data access code or troubleshooting Azure SQL performance will find the setup details useful.