# ORM Published articles for ORM. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Building async Python applications with Tortoise ORM and Amazon Aurora DSQL DevFeed: [Building async Python applications with Tortoise ORM and Amazon Aurora DSQL]() Original publisher: [Read original article]() Author: Lasita Bhattacharya Published: 2026-09-09T15:27:43Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [DSQL](), [Concurrency](), [AWS IAM](), [Database](), [CRUD]() Tags: [advanced-300](), [amazon-aurora](), [concurrency](), [database](), [dsql](), [how-to](), [iam](), [orm](), [postgresql](), [python](), [rideshare](), [serverless](), [technical-how-to]() ### AI overview A tutorial for building a high-concurrency asynchronous Python rideshare application with Tortoise ORM and Amazon Aurora DSQL. It covers UUID-based models, IAM-authenticated asyncpg connections, OCC retry handling, and asynchronous CRUD operations. ### Source excerpt Build a high-concurrency async Python rideshare application with Tortoise ORM and Amazon Aurora DSQL. This post walks through the key adaptations: UUID primary keys, IAM-authenticated asyncpg connections with a connection-pool patch, individual DDL execution, and optimistic concurrency control (OCC) retry logic. ## Use Drizzle ORM with Appwrite Postgres DevFeed: [Use Drizzle ORM with Appwrite Postgres]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-09-08T00:00:00Z Content type: tutorial Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Drizzle](), [migration](), [Object-relational mapping](), [PostgreSQL](), [TypeScript](), [Databases](), [SQL]() Tags: [data](), [drizzle](), [migration](), [migrations](), [orm](), [postgres](), [postgresql](), [schema](), [sql](), [tutorials](), [typescript]() ### AI overview A tutorial showing how to connect Drizzle ORM to Appwrite Postgres, define tables and queries in TypeScript, generate and apply SQL migrations, seed data, and evolve a schema while preserving existing records. ### Source excerpt Connect Drizzle ORM to Appwrite Postgres, query data with TypeScript, and apply SQL migrations as your schema changes. ## SymfonyCon Warsaw 2026: Unveiling the workshop lineup! DevFeed: [SymfonyCon Warsaw 2026: Unveiling the workshop lineup!]() Original publisher: [Read original article]() Author: Eloïse Charrier Published: 2026-09-07T15:35:00Z Content type: news Language: en Sources: [Symfony Blog]() Topics: [Deployment](), [Kubernetes](), [Architecture & Design](), [Refactoring](), [dashboards](), [Vulnerabilities](), [Web Development]() Tags: [agentic](), [ai](), [architecture](), [community](), [deep-dive](), [deployment](), [developer](), [javascript](), [kubernetes](), [news](), [observability](), [orm](), [php](), [production](), [refactoring](), [security](), [symfony](), [vulnerabilities](), [workflows](), [workshops]() ### AI overview SymfonyCon Warsaw 2026 announces its workshop lineup, covering Symfony 8, Kubernetes deployment, clean-architecture refactoring, Doctrine ORM, Symfony AI, Symfony UX, threat modeling, and production observability. Workshops take place on November 24 and 25 in Warsaw, ahead of the main conference. ### Source excerpt We are counting down to SymfonyCon Warsaw 2026, taking place on November 26-27, 2026, in Warsaw (Poland)! Get ready for a week full of workshops, sessions, and community magic. Great news today: all workshops are now online and open for registration!... ## Native databases vs Appwrite databases: which one should you pick? DevFeed: [Native databases vs Appwrite databases: which one should you pick?]() Original publisher: [Read original article]() Author: Atharva Deosthale Published: 2026-09-01T00:00:00Z Content type: tutorial Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Databases](), [MySQL](), [PostgreSQL](), [SDKs]() Tags: [api](), [backend](), [comparisons](), [databases](), [guide](), [mysql](), [orm](), [postgresql](), [realtime](), [transactions]() ### AI overview This guide compares Appwrite's managed TablesDB, DocumentsDB, and VectorsDB with native PostgreSQL and MySQL databases. It explains the trade-off between Appwrite's SDK-based permissions, realtime events, functions, and other platform features and the direct SQL access available through native database drivers or ORMs. ### Source excerpt Appwrite offers two kinds of databases. This guide explains how TablesDB, DocumentsDB, and VectorsDB differ from native PostgreSQL and MySQL, and how to choose between them for your project. ## Soft deletes affect database constraints, indexes, and application queries DevFeed: [Soft deletes affect database constraints, indexes, and application queries]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-08-20T00:00:00Z Content type: opinion Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [data-processing](), [Database](), [MySQL]() Tags: [data-modelling](), [database-design](), [foreign-keys](), [indexes](), [indexing](), [mysql](), [orm](), [postgresql](), [predicate](), [schema](), [schema-design](), [soft-delete]() ### AI overview The article explains how soft deletion affects database design beyond adding a deleted_at column. It discusses duplicate-key failures, foreign-key behavior, queries that may return deleted rows, and index inefficiency, noting that PostgreSQL partial indexes help while MySQL requires a workaround. ### Source excerpt A deleted_at column turns every future query into a conditional one, and the cost is not the extra predicate. Unique constraints stop working because the deleted row still occupies the key, foreign keys start pointing at rows the application considers gone, and any query written by someone who does not know about the column silently returns deleted data. Soft delete is a data lifecycle decision, and treating it as a boolean column is what makes it expensive. ## How ORM N+1 Queries Create Hidden Request Latency DevFeed: [How ORM N+1 Queries Create Hidden Request Latency]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-08-02T00:00:00Z Content type: tutorial Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [Object-relational mapping](), [Latency](), [Monitoring](), [lazy loading](), [Database](), [connection pool]() Tags: [connection-pool](), [database](), [database-performance](), [hibernate](), [latency](), [lazy-loading](), [monitoring](), [n-plus-one](), [observability](), [orm](), [query](), [request]() ### AI overview This article explains how ORM lazy loading can turn a loop over orders into an N+1 query pattern. Individual queries may remain fast and avoid slow-query alerts, while the accumulated network round trips increase request latency and hold connection-pool resources. It recommends monitoring queries per request and asserting query counts in tests. ### Source excerpt N+1 queries hide from monitoring because no individual query is slow. Four hundred queries at 0.4ms each never appear in the slow query log, never move p99 query latency, and still cost the request 300ms because the expense is the round trip rather than the execution. The metric that catches it is queries per request, and the only durable fix is asserting on that count in tests, since the code that causes it looks like a field access rather than I/O. ## The Real Python Podcast - Episode #305: Should You Understand Your Entire Python Codebase? DevFeed: [The Real Python Podcast - Episode #305: Should You Understand Your Entire Python Codebase?]() Original publisher: [Read original article]() Author: Real Python Published: 2026-07-31T12:00:00Z Content type: article Language: en Sources: [Real Python]() Topics: [Code](), [releases]() Tags: [code](), [django](), [orm](), [podcast](), [python](), [releases](), [rust]() ### AI overview A podcast episode about whether developers need to understand an entire Python codebase, Python built-in functions, and selected Python community news and resources. ### Source excerpt Should you understand the entirety of your codebase? How familiar are you with Python's built-in functions? Christopher Trudeau is back on the show this week with another batch of PyCoder's Weekly articles and projects. ## When Clean Architecture Overhead Is Justified in Larger Projects DevFeed: [When Clean Architecture Overhead Is Justified in Larger Projects]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-07-28T06:01:50Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [Software](), [Object-relational mapping](), [Databases]() Tags: [architecture](), [clean-architecture](), [database](), [databases](), [developer](), [developers](), [orm](), [software]() ### AI overview The article argues that Clean Architecture adds real overhead through extra interfaces, abstractions, indirection, and separate domain and ORM entities. It contends that this trade-off becomes worthwhile as midsize and enterprise projects grow, because decoupling business logic from infrastructure and database structures makes change easier. ### Source excerpt Stop counting lines of code ## Learning a few things about running SQLite DevFeed: [Learning a few things about running SQLite]() Original publisher: [Read original article]() Author: Julia Evans Published: 2026-07-17T00:00:00Z Content type: article Language: en Sources: [Julia Evans]() Topics: [SQLite](), [Django](), [Object-relational mapping](), [Query (disambiguation)](), [Statistics]() Tags: [blog](), [django](), [orm](), [search](), [sqlite](), [statistics]() ### AI overview A personal account of operating SQLite in production for a small Django website. The article describes how running ANALYZE dramatically improved an SQLite FTS5 query and discusses the difficulty of cleaning up large numbers of rows without blocking other database writers. ### Source excerpt Hello! I've been working on a Django site recently, and I decided to use SQLite as the database. When I was getting started with using SQLite as database for a website I read a bunch of blog posts about how it is totally fine to use SQLite in production for a small site and I think it is totally fine, but what I did not fully appreciate is that SQLite is still a database, databases are complicated, and I do not know a lot about operating databases. So here are a couple of small things I've been learning about running SQLite. This is the 4th website I've used SQLite for, and I think this one is harder because with the power of the Django ORM I've been making the database do more work than I was previously without Django. I started by turning on WAL mode like all the blog posts said to do and hoping for the best. ANALYZE is apparently important Today I was running a query (using SQLite's FTS5 for full-text search) on a table with 4000 rows and it took 5 seconds. That seemed wrong to me: computers are fast! It turned out that what I needed to do was to run ANALYZE! Immediately the problem query went from taking 5 seconds to like 0.05 seconds (or some other number small enough that I didn't care to investigate further). I still don't know exactly what went wrong in the query plan, but my best guess is that it was some sort of accidentally quadratic thing. ANALYZE generates "statistics" (I guess about the number of rows in each table? and presumably other things?) so that the query planner can make better choices. Maybe one day I'll learn to read a query plan. cleaning up the database is tricky Occasionally I've run into situations where I accidentally put a bunch of rows in my database that I don't want to be there (for example completed tasks from django-tasks-db), and I want to clean them up. What's happened to me a few times in this case is: I run some kind of command to clean up the rows The command takes more than 5 seconds, since there are a lot of rows (though I ## Clean Architecture Mistake: ORM ≠ Domain DevFeed: [Clean Architecture Mistake: ORM ≠ Domain]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-07-09T06:02:30Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [Object-relational mapping]() Tags: [architecture](), [clean-architecture](), [orm]() ### AI overview The article warns that ORM entities should not be confused with domain entities. ### Source excerpt Do NOT confuse ORM entities with domain entities. ## OpenAPI, ORM, SVG and Lottie DevFeed: [OpenAPI, ORM, SVG and Lottie]() Original publisher: [Read original article]() Author: Shai Almog Published: 2026-06-01T00:00:00Z Content type: release Language: en Sources: [CodeName One]() Topics: [OpenAPI Specification](), [Code generation](), [SQLite](), [Object-relational mapping](), [JSON](), [XML](), [SVG](), [ASP.NET Core](), [FastAPI](), [Nest]() Tags: [build](), [fastapi](), [http](), [java](), [json](), [lottie](), [maven-plugin](), [net](), [openapi](), [orm](), [rest](), [spring](), [svg](), [xml]() ### AI overview A Codename One release follow-up describes a shared build-time code generation pipeline for OpenAPI client generation, a SQLite ORM, JSON and XML mappers, SVG and Lottie transcoders, and a declarative router. The pipeline emits typed Java from annotations or declarative source files without reflection. ### Source excerpt An OpenAPI client generator, a JPA-shaped SQLite ORM, JAXB-shaped JSON / XML mappers, build-time SVG / Lottie transcoders, and a declarative router with deep links. All on the same build-time codegen pipeline. ## NetBox Config Templates Tip: Query Objects Efficiently with .filter() DevFeed: [NetBox Config Templates Tip: Query Objects Efficiently with .filter()]() Original publisher: [Read original article]() Author: Rick Donato Published: 2026-03-10T08:00:07Z Content type: tutorial Language: en Sources: [Packet Coders - Learn Network Automation]() Topics: [NetBox](), [Django](), [Object-relational mapping]() Tags: [config](), [django](), [filter](), [interface](), [interfaces](), [netbox](), [orm](), [query](), [templates](), [tips]() ### AI overview A short tutorial showing how to use .filter() in NetBox Config Templates to query objects during lookups and conditional logic through the Django ORM QuerySet interface. ### Source excerpt Use .filter() in Config Templates to query objects during lookups and conditional logic. This exposes the Django ORM QuerySet filter directly in your templates. Here's an example: {% for iface in device.interfaces.filter(enabled=True, name__startswith="ge-") %} interface {{ iface.name }} {% endfor %} ## ClickHouse.Driver 1.0.0: The Official .NET Client Hits Stable DevFeed: [ClickHouse.Driver 1.0.0: The Official .NET Client Hits Stable]() Original publisher: [Read original article]() Author: Alex Soffronow Pagonidis Published: 2026-03-02T12:02:31Z Content type: release Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [.NET](), [API](), [NuGet](), [OpenTelemetry](), [JSON Web Tokens](), [JSON](), [Object-relational mapping]() Tags: [api](), [authentication](), [c-sharp](), [clickhouse](), [json](), [net](), [nuget](), [observability](), [orm](), [release](), [releases](), [tracing]() ### AI overview ClickHouse.Driver 1.0.0 is the first stable official .NET client for ClickHouse. The release adds a stable ClickHouseClient API, broad type support, NuGet signing, JWT authentication, JSON-column serialization, OpenTelemetry integration, and documentation with more than 40 usage examples. ### Source excerpt We are proud to announce the release of ClickHouse.Driver 1.0.0, the first stable release of the official .NET client for ClickHouse. ## Some notes on starting to use Django DevFeed: [Some notes on starting to use Django]() Original publisher: [Read original article]() Author: Julia Evans Published: 2026-01-27T00:00:00Z Content type: article Language: en Sources: [Julia Evans]() Topics: [Django](), [Framework](), [Object-relational mapping](), [Website](), [Database](), [Rails](), [Laravel]() Tags: [database](), [django](), [framework](), [laravel](), [orm](), [rails](), [web]() ### AI overview A developer shares notes from starting to use Django after previously trying Rails. They find Django's explicit project structure easier to return to after long breaks, appreciate its built-in and customizable admin interface, and are enjoying its ORM for expressing database relationships and queries with less code. ### Source excerpt Hello! One of my favourite things is starting to learn an Old Boring Technology that I've never tried before but that has been around for 20+ years. It feels really good when every problem I'm ever going to have has been solved already 1000 times and I can just get stuff done easily. I've thought it would be cool to learn a popular web framework like Rails or Django or Laravel for a long time, but I'd never really managed to make it happen. But I started learning Django to make a website a few months back, I've been liking it so far, and here are a few quick notes! less magic than Rails I spent some time trying to learn Rails in 2020, and while it was cool and I really wanted to like Rails (the Ruby community is great!), I found that if I left my Rails project alone for months, when I came back to it it was hard for me to remember how to get anything done because (for example) if it says resources :topics in your routes.rb, on its own that doesn't tell you where the topics routes are configured, you need to remember or look up the convention. Being able to abandon a project for months or years and then come back to it is really important to me (that's how all my projects work!), and Django feels easier to me because things are more explicit. In my small Django project it feels like I just have 5 main files (other than the settings files): urls.py, models.py, views.py, admin.py, and tests.py, and if I want to know where something else is (like an HTML template) is then it's usually explicitly referenced from one of those files. a built-in admin For this project I wanted to have an admin interface to manually edit or view some of the data in the database. Django has a really nice built-in admin interface, and I can customize it with just a little bit of code. For example, here's part of one of my admin classes, which sets up which fields to display in the "list" view, which field to search on, and how to order them by default. @admin.register(Zine) class ZineAdmin(adm ## The Hidden Cost of Convenience: Rethinking Old ORM Patterns for Scale DevFeed: [The Hidden Cost of Convenience: Rethinking Old ORM Patterns for Scale]() Original publisher: [Read original article]() Author: Andrew Houts Published: 2025-12-08T22:06:50Z Content type: article Language: en Sources: [Wealthfront]() Topics: [Object-relational mapping](), [Code](), [data](), [Tooling](), [dashboards](), [Database](), [Concurrency]() Tags: [backend](), [best-practices](), [code](), [data](), [database](), [flame-graph](), [orm](), [parallelism](), [performance](), [profiling](), [sql](), [tooling](), [wealthfront-engineering]() ### AI overview Wealthfront examines performance problems in an aging portfolio balance calculation system whose overnight batch processing scaled poorly as client growth and assets under management increased. The article describes profiling the job with command-line and sampling-profiler tools, using collected data and flame graphs to investigate where runtime was spent. ### Source excerpt Ever been here before? Stuck with a job that needs to be continually revisited because its performance gets worse with every passing day, and each attempt at improving said performance yields diminishing returns? This is the situation we found ourselves in with the portfolio balance calculation system--the code responsible for aggregating data from multiple sources... Read more ## AI Rules: Bring Neon Context into Your Editor DevFeed: [AI Rules: Bring Neon Context into Your Editor]() Original publisher: [Read original article]() Author: Carlota Soto Published: 2025-09-02T18:00:24Z Content type: tutorial Language: en Sources: [Blog -- Neon Docs]() Topics: [ai-coding](), [cursor](), [Authentication](), [Serverless](), [Transactions](), [Next.js](), [Database]() Tags: [ai](), [ai-coding](), [auth](), [authentication](), [best-practices](), [cursor](), [next-js](), [orm](), [postgres](), [product](), [serverless](), [transactions](), [workflow]() ### AI overview The article introduces Neon-specific AI rules that can be added to editors such as Cursor. These rules provide context-aware guidance for full-stack applications, including authentication with Stack Auth and Neon Auth, Next.js setup, route protection, serverless connections, transaction handling, and avoiding hardcoded credentials. ### Source excerpt Using AI coding assistants like Cursor to build your full-stack apps makes for a powerful workflow, but they don't always know the specifics of every tool - including Neon - and can do a little help. To give your editor Neon-specific context and help it generate better code from... ## Common Foreign Key Pitfalls and Optimizations in Django DevFeed: [Common Foreign Key Pitfalls and Optimizations in Django]() Original publisher: [Read original article]() Author: Haki Benita Published: 2025-07-14T21:00:00Z Content type: article Language: en Sources: [Haki Benita]() Topics: [Django](), [Code](), [implementation]() Tags: [article](), [articles](), [deprecated](), [django](), [documentation](), [how-to](), [orm](), [pitfalls](), [review]() ### AI overview An article about foreign keys in Django that demonstrates common pitfalls, potential optimizations, and implicit behavior. It uses a product catalog example and discusses constraints, auditing fields, ordering, and replacing deprecated unique_together usage with UniqueConstraint. ### Source excerpt Constraints keep the integrity of your system and prevent you from shooting yourself in the foot. Foreign keys are a special type of constraint because, unlike unique, check, and primary keys, they span more than one relation. This makes foreign keys harder to enforce and harder to get right. In this article, I demonstrate common pitfalls, potential optimizations, and implicit behavior related to foreign keys. ## Building a Multi-Tenant Architecture Platform to Scale the Emmys DevFeed: [Building a Multi-Tenant Architecture Platform to Scale the Emmys]() Original publisher: [Read original article]() Author: Ana Tavares Published: 2025-06-24T11:40:00Z Content type: article Language: en Sources: [Laravel Blog]() Topics: [web applications]() Tags: [architecture](), [http](), [laravel](), [multi-tenancy](), [orm](), [platform](), [scale]() ### AI overview The article explains how Crowd Favorite built Orthicon, a Laravel-based multi-tenant platform for Emmy competitions. It uses tenant tokens in custom HTTP headers and Laravel middleware to route requests while keeping tenant data and configuration logically isolated. ### Source excerpt How Crowd Favorite built their multi-tenant Emmy Awards management platform and scaled it to handle user spikes of up to 570%. ## Neon Launchpad: A Tool For Instant Postgres, No Login Needed DevFeed: [Neon Launchpad: A Tool For Instant Postgres, No Login Needed]() Original publisher: [Read original article]() Author: Atila Fassina Published: 2025-06-06T17:57:34Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [Provisioning](), [Tooling](), [Command-line interface](), [Object-relational mapping](), [Open Source](), [AI Agent]() Tags: [agent](), [ai](), [building](), [cli](), [company](), [developer](), [open-source](), [orm](), [postgres](), [product](), [provisioning](), [tool]() ### AI overview Neon Launchpad provides real hosted Postgres databases in seconds without requiring setup, login, or configuration. It is designed for developer tools, templates, platforms, open-source projects, scaffolding tools, and AI agents that need on-demand databases. Users receive a connection string compatible with Postgres tools, frameworks, ORMs, and SQL clients; databases last 72 hours by default and can later be claimed through a Neon account. ### Source excerpt If you're building a dev tool, template, or platform where users need a database, you're probably familiar with the pain: you can either ask them to bring their own, or build a full provisioning flow yourself. Beyond just provisioning it, your users will need to set up their sche... ## Migrating From PostgreSQL to MongoDB in a .NET EF Core Application DevFeed: [Migrating From PostgreSQL to MongoDB in a .NET EF Core Application]() Original publisher: [Read original article]() Author: Luce Carter Published: 2025-05-01T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [PostgreSQL](), [.NET](), [Object-relational mapping](), [migration](), [Databases](), [Development]() Tags: [algorithms](), [azure](), [dotnet](), [efcore](), [genai](), [migration](), [mongodb](), [net](), [orm](), [postgres](), [postgresql](), [relational-databases]() ### AI overview This tutorial explains how to migrate a .NET application using PostgreSQL and Entity Framework Core to MongoDB with the MongoDB EF Core Provider. It also describes using Relational Migrator to transform relational data and model it for MongoDB collections. ### Source excerpt For many reasons--including scalability, flexibility, and modernization--more and more development teams are looking to migrate away from PostgreSQL to MongoDB. In the past, these teams might have been ... The post Migrating From PostgreSQL to MongoDB in a .NET EF Core Application appeared first on DEV. ## Scaling Nextdoor's Datastores: Part 2 DevFeed: [Scaling Nextdoor's Datastores: Part 2]() Original publisher: [Read original article]() Author: Tushar Singla Published: 2025-03-19T15:08:32Z Content type: article Language: en Sources: [Nextdoor]() Topics: [Database](), [Replication](), [Django](), [Object-relational mapping](), [consistency](), [race-condition](), [Transactions]() Tags: [consistency](), [database](), [database-scalability](), [django](), [orm](), [race-condition](), [rdbms](), [read-replica](), [replication](), [transactions]() ### AI overview The second installment of Nextdoor's datastore-scaling series examines the consistency problems caused by database read replicas. It describes how routing decisions became obscured by Django ORM abstractions, leading to read-after-write races, and explains how transactions were used as a workaround with negative effects on database load. ### Source excerpt In the second installment of Nextdoor's "Scaling Nextdoor's Datastores" blog series, the Core-Services team discusses challenges faced after implementing database read replicas. Adding read replicas to an existing database is a very common pattern as applications or products evolve to handle increased demand. Typically, the implementation details are hand waved and it's assumed that this strategy will work. However, that is rarely the case, and we'll dive into some more of the intricacies around the implementation. Initial Attempt When replicas were first introduced in the Nextdoor stack, we gave the product engineers latitude to choose when they wanted to have their query routed to a read replica or to the primary. This was done by leveraging the existing routing mechanism in our ORM, Django. This seemed like the right idea at the time because the product engineers had the most context around consistency requirements within their changes and load characteristics of their product feature. Therefore, they would have the best ability to judge which node to send their query to. However, as our business logic evolved and became more feature-rich, product engineers began to add abstraction layers to help abstract complex operations away from business logic. In this design evolution there is a high frequency read, followed by a low frequency conditional write, followed by a read. The read performed after the write should be routed to the primary, but that may get buried in abstractions and this requirement regressed. The explicit routing decisions engineers made became buried and subsequently created a serious problem for users of these abstractions. If one abstraction method was performing a write and another a read, they could not safely be used together due to read-after-write consistency issues. Due to replication lag between the primary and replica databases, a race condition arises when the application attempts to read data from a replica after performing a write. W ## Launch Postgres in Your Browser, Keep It On Neon DevFeed: [Launch Postgres in Your Browser, Keep It On Neon]() Original publisher: [Read original article]() Author: Guillaume Rivals Published: 2025-01-23T19:32:26Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [Serverless](), [Cloudflare Workers](), [Workers](), [Drizzle](), [React Router](), [Provisioning](), [autoscaling](), [API](), [Command-line interface]() Tags: [api](), [autoscaling](), [browser](), [cli](), [cloudflare](), [cloudflare-workers](), [drizzle](), [launch](), [orm](), [postgres](), [provisioning](), [serverless]() ### AI overview Instagres lets users launch a functional Postgres database in a browser or through a CLI without containers, infrastructure setup, or an account. Users can later transfer the database to a free Neon account to keep it persistent. ### Source excerpt Sometimes you need a Postgres database right now, and you'd like to have it without setting up containers, deploying infra, or creating an account anywhere. Maybe you're following a tutorial online or testing a quick idea. Enter Instagres--a tool that lets you spin up a fully func... ## Announcing Laravel Support and PHP PDO Interface DevFeed: [Announcing Laravel Support and PHP PDO Interface]() Original publisher: [Read original article]() Author: Levy Albuquerque Published: 2025-01-09T00:00:00Z Content type: release Language: en Sources: [Turso Blog]() Topics: [Laravel](), [Turso](), [PHP](), [libSQL](), [PHP Data Objects (PDO)](), [Composer](), [Eloquent ORM](), [Object-relational mapping](), [SQLite](), [Embeddings](), [Query (disambiguation)](), [migration]() Tags: [database](), [embeddings](), [features](), [laravel](), [libsql](), [orm](), [php](), [recommendation-system](), [sdk](), [sdks](), [sqlite](), [turso]() ### AI overview Turso announces official Laravel support through the open-source libsql-laravel adapter and PHP PDO interface. The technical preview integrates with Laravel's database layer, supports local SQLite and Turso configurations, and removes the need for custom PHP extensions. The article also demonstrates migrations, Eloquent models, vector embeddings, and similarity searches for a movie recommendation system. ### Source excerpt Use Turso natively with Laravel through our new 'libsql-laravel' adapter and PHP PDO interface. No custom PHP extensions, just a database URL and auth token. ## Announcing Inertia 2.0: Redefining Frontend Development for Laravel DevFeed: [Announcing Inertia 2.0: Redefining Frontend Development for Laravel]() Original publisher: [Read original article]() Author: Joe Tannenbaum Published: 2024-12-13T19:28:00Z Content type: release Language: en Sources: [Laravel Blog]() Topics: [Laravel](), [frontend development](), [Front end](), [Single-page application (SPA)](), [React](), [Svelte](), [Vue.js](), [Object-relational mapping](), [Routing (disambiguation)](), [Core Web Vitals]() Tags: [async](), [core-web-vitals](), [deferred](), [frontend-development](), [laravel](), [lazy-loading](), [orm](), [performance](), [react](), [release](), [routing](), [svelte](), [vue]() ### AI overview Inertia 2.0 is a stable release that adds asynchronous requests, deferred props, prefetching, and polling to Laravel frontend development. These features support more responsive applications while avoiding the complexity of maintaining a separate API. ### Source excerpt Inertia 2.0 brings powerful new features to Laravel frontend development including async requests, deferred props, prefetching, and polling. Learn how these improvements help you build faster, more responsive applications without the complexity of maintaining a separate API. [Next page]()