# MongoDB MongoDB is a document database for building applications. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Mongorewind: Rewind Your MongoDB Test Data Without Restoring a Backup DevFeed: [Mongorewind: Rewind Your MongoDB Test Data Without Restoring a Backup]() Original publisher: [Read original article]() Author: Zelmar Michelini Published: 2026-09-02T11:38:40Z Content type: tutorial Language: en Sources: [Blog - Percona]() Topics: [MongoDB](), [Terminal](), [Command-line interface](), [ci](), [dashboards](), [Streams]() Tags: [ci](), [code](), [commands](), [database](), [mongodb](), [state](), [terminal](), [tests](), [ui]() ### AI overview This article introduces mongorewind, a terminal UI tool that records MongoDB data changes through a cluster-wide change stream and reverses them in reverse chronological order. It is designed to restore test data to its pre-test state without restoring a backup and supports interactive and CI use. ### Source excerpt Mongorewind: Rewind Your MongoDB Test Data Without Restoring a Backup One day, my friend Martín told me about a problem he and his team were dealing with. Every time they needed to run a pre-production test, they had to restore a copy of the production database into their test cluster. That process alone takes about ... Continued The post Mongorewind: Rewind Your MongoDB Test Data Without Restoring a Backup appeared first on Percona. ## How Yandex Tracker reduced its MongoDB cluster count from 70 to 7 DevFeed: [How Yandex Tracker reduced its MongoDB cluster count from 70 to 7]() Original publisher: [Read original article]() Author: onurimanov (Яндекс) Published: 2026-09-02T07:00:24Z Content type: article Language: ru Sources: [Яндекс - Как мы делаем Яндекс / Статьи]() Topics: [MongoDB](), [базы данных](), [яндекс]() Tags: [architecture](), [migration](), [mongodb](), [tag-1cd610c0e518](), [tag-39f0c170b680](), [tag-4004cf5948d3](), [tag-5335b6f99fba](), [tag-56a552acf7d0](), [tag-622612a5798e](), [tag-68e701e78517](), [tag-89f0c6f39f5d](), [tag-9d8cf70dc46c](), [tag-d189f87ebb8f]() ### AI overview A technical article describes how Yandex Tracker changed its data-storage architecture from one database per organization to a model using fewer backend clusters. The change reduced the number of backend clusters from 70 to 7 and cut resource consumption by half, while addressing operational complexity and MongoDB collection limits. ### Source excerpt Разворачивать новый кластер базы данных каждую неделю -- так себе удовольствие, особенно когда обслуживание десятков кластеров съедает время дежурных. Когда кластеров стало много, локальные аномалии стало сложнее замечать на общих дашбордах. С этой проблемой мы столкнулись в Яндекс Трекере: за год количество активных организаций и кластеров выросло вдвое, а нагрузка на сервис поднялась всего на 13%. Получилось парадоксально: потребление ресурсов и сложность эксплуатации росли вместе с числом организаций, хотя реальная нагрузка увеличивалась значительно медленнее. Читать далее ## Rotating Expiring X.509 Certificates in Percona Server for MongoDB with Minimal Service Interruption DevFeed: [Rotating Expiring X.509 Certificates in Percona Server for MongoDB with Minimal Service Interruption]() Original publisher: [Read original article]() Author: Ivan Groenewold Published: 2026-08-31T11:48:11Z Content type: tutorial Language: en Sources: [Blog - Percona]() Topics: [MongoDB](), [TLS (Transport Layer Security)](), [Authentication](), [configuration]() Tags: [authentication](), [certificates](), [insight-for-dbas](), [mongodb](), [private-key](), [rotation](), [security](), [tls](), [x509]() ### AI overview This tutorial explains how to renew same-CA X.509 certificates in Percona Server for MongoDB with minimal service interruption. It covers reloading TLS material with rotateCertificates, certificate and private-key configuration, limitations, validation, and cases where hot reload should not be used. ### Source excerpt Expired TLS certificates can prevent new client connections and, when X.509 is used for Percona Server for MongoDB internal authentication, also prevent members of a replica set or sharded cluster from authenticating to one another. In this post we will discuss performing a same-CA renewal: replacement certificates for server, member, and client leaf are issued ... Continued The post Rotating Expiring X.509 Certificates in Percona Server for MongoDB with Minimal Service Interruption appeared first on Percona. ## How MongoDB Atlas and Temporal support reliable production RAG and AI agents DevFeed: [How MongoDB Atlas and Temporal support reliable production RAG and AI agents]() Original publisher: [Read original article]() Author: Suresh Ramappa Published: 2026-08-13T00:00:00Z Content type: opinion Language: en Sources: [Temporal Blog]() Topics: [MongoDB](), [Retrieval Augmented Generation (RAG)](), [AI Infrastructure](), [Artificial Intelligence](), [reliability]() Tags: [agentic](), [agents](), [ai](), [ai-infrastructure](), [api](), [data](), [embeddings](), [long-running](), [mongodb](), [outages](), [pipelines](), [production](), [rag](), [recovery](), [reliability](), [retries](), [retrieval](), [temporal-voices]() ### AI overview The article argues that MongoDB Atlas and Temporal address different reliability needs in production RAG and AI agent systems. Atlas provides operational data, embeddings, vector search, and agent memory in one platform, while Temporal provides durable execution for crash recovery, retries, and long-running ingestion and agent workflows. ### Source excerpt Why MongoDB Atlas and Temporal are better together for AI: one data platform, one durable execution layer, for RAG and agents in prod. ## Introducing Enterprise Flexible Commitment for Vercel Marketplace DevFeed: [Introducing Enterprise Flexible Commitment for Vercel Marketplace]() Original publisher: [Read original article]() Author: Hedi Zandi Published: 2026-07-30T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel](), [Supabase](), [MongoDB](), [Redis]() Tags: [cost](), [customers](), [documentation](), [enterprise](), [infrastructure](), [integrations](), [mongodb](), [pricing](), [redis](), [vercel]() ### AI overview Vercel now allows Enterprise customers to use part of their Flexible Commitment for eligible resources purchased through the Vercel Marketplace. The initial supported partners include Neon, Supabase, MongoDB, and Redis, with more providers planned. ### Source excerpt Enterprise customers can now apply a portion of their Flexible Commitment toward eligible resources purchased through the Vercel Marketplace. With Flex Commit support, eligible Marketplace cost can draw directly from your existing commitment making it easier to provision the infrastructure and services your applications need. We're rolling this out with an initial set of Marketplace partners, including Neon, Supabase, Mongodb and Redis, with support for more providers coming. Eligible integrations are marked with a Flexible Commitment Eligible badge on their Marketplace page. With Marketplace Flex Commit you can: Use committed Enterprise spend for eligible Marketplace resources Eliminate separate credit card or procurement workflows Provision and manage third-party services directly from the Vercel Marketplace Track Marketplace usage alongside the rest of your Enterprise commitment This is the first step toward making the Marketplace a seamless part of the Enterprise experience. To learn more, read our pricing page documentation and reach out to your Account Manager. Read more ## MongoDB Query Tracing in .NET with Sentry + OTLP DevFeed: [MongoDB Query Tracing in .NET with Sentry + OTLP]() Original publisher: [Read original article]() Author: James Crosswell Published: 2026-07-20T09:00:00Z Content type: tutorial Language: en Sources: [Sentry Blog]() Topics: [MongoDB](), [OpenTelemetry](), [tracing](), [.NET](), [telemetry](), [SDK]() Tags: [instrumentation](), [integration](), [mongodb](), [net](), [opentelemetry](), [sdk](), [telemetry](), [traces](), [tracing]() ### AI overview This tutorial demonstrates how to trace MongoDB queries in a .NET application by combining MongoDB's built-in OpenTelemetry instrumentation with Sentry's OTLP ingestion support in the .NET SDK. It explains how MongoDB spans and query data can flow into Sentry for performance analysis and correlation with errors and replays. ### Source excerpt Trace MongoDB queries in .NET using OpenTelemetry and Sentry's OTLP ingestion. See spans, query data, and error correlation in Sentry. ## What's new in two: June 2026 edition DevFeed: [What's new in two: June 2026 edition]() Original publisher: [Read original article]() Author: Talon Miller Published: 2026-07-06T00:00:00Z Content type: release Language: en Sources: [Redis Blog]() Topics: [Redis](), [releases](), [Amazon Web Services](), [Iris](), [MongoDB](), [real-time](), [REST API](), [Latency](), [personalization](), [Artificial Intelligence]() Tags: [2026](), [ai-agents](), [api](), [aws](), [cloud](), [data](), [latency](), [mongodb](), [performance](), [personalization](), [redis](), [releases](), [rest-api](), [tech](), [updates]() ### AI overview Redis's June 2026 release roundup highlights the general availability of Redis Data Integration in Redis Cloud on AWS. RDI continuously syncs operational data into Redis for applications, services, and AI workloads, with improved provisioning, visibility, error reporting, synchronization performance, source configuration, and Redis Cloud REST API management. The update adds MongoDB support and preview support for Snowflake, enabling application acceleration, real-time decisioning, personalization, recommendations, fraud detection, and AI-driven workflows. The article also begins describing a Flex update focused on infrastructure cost and performance. ### Source excerpt Welcome back to "What's new in two," your quick hit of Redis releases you might've missed over the last month. Summer might be here, but product releases apparently don't take vacations. We're covering the biggest updates from June and expanding on wh... ## How Zernio scaled to 6M daily posts on a 7-person team with Tinybird DevFeed: [How Zernio scaled to 6M daily posts on a 7-person team with Tinybird]() Original publisher: [Read original article]() Author: Tinybird Published: 2026-06-25T12:00:00Z Content type: article Language: en Sources: [Tinybird]() Topics: [data](), [API](), [MongoDB](), [Latency]() Tags: [api](), [customer-stories](), [data](), [latency](), [mongodb](), [time]() ### AI overview A case study describes how Zernio moved its analytics from MongoDB to Tinybird, reduced the time required to ship new data features from weeks to hours, and handles 700,000 daily API requests with p95 latency of 250 milliseconds. ### Source excerpt Learn how Zernio moved analytics from MongoDB to Tinybird, cut time to ship new data features from weeks to hours, and now handles 700,000 daily API requests with p95 latency of 250ms. ## How Spyne simplified their CDC pipeline with ClickPipes and ClickHouse Cloud DevFeed: [How Spyne simplified their CDC pipeline with ClickPipes and ClickHouse Cloud]() Original publisher: [Read original article]() Author: ClickHouse Published: 2026-06-22T11:37:29Z Content type: article Language: en Sources: [ClickHouse Blog]() Topics: [clickhouse](), [schema-evolution](), [Kafka](), [MongoDB](), [MySQL](), [Streaming](), [developer velocity](), [Serverless](), [Cloud](), [real-time](), [DevOps]() Tags: [clickhouse](), [cloud-infrastructure](), [data](), [developer-velocity](), [devops](), [kafka](), [mysql](), [open-source](), [real-time](), [schema-evolution](), [serverless](), [streaming]() ### AI overview Spyne migrated its change data capture pipeline from a self-managed Debezium and Kafka stack to serverless ClickPipes and ClickHouse Cloud. The change reduced table onboarding time from more than 1.5 hours to minutes and automated schema evolution, improving data consistency and developer velocity. ### Source excerpt Spyne cut table onboarding from 1.5+ hours to minutes and eliminated schema drift by migrating their CDC pipeline from a self-managed Debezium/Kafka stack to ClickPipes and ClickHouse Cloud. ## Test Password Strength and Password History with TypeScript and MongoDB DevFeed: [Test Password Strength and Password History with TypeScript and MongoDB]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-06-19T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [passwords](), [MongoDB](), [TypeScript](), [Authentication](), [Development](), [Express](), [Node.js](), [API]() Tags: [api](), [authentication](), [development](), [express](), [getting-started](), [how-to](), [mongodb](), [node](), [password](), [tutorial](), [typescript]() ### AI overview A tutorial on building a TypeScript API with Express and MongoDB that enforces password-strength rules, stores current and previous password hashes, authenticates users, and rejects password reuse. ### Source excerpt Just about every application you build is going to need some form of user authentication, and the moment you have user accounts, you have passwords to manage. Storing them safely is only part of the j... The post Test Password Strength and Password History with TypeScript and MongoDB appeared first on DEV. ## How to Install MongoDB on Ubuntu: A Step-by-Step Guide for Beginners DevFeed: [How to Install MongoDB on Ubuntu: A Step-by-Step Guide for Beginners]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-06-06T02:40:24Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [Ubuntu](), [Linux](), [Package manager](), [Command-line interface]() Tags: [command-line](), [guide](), [how-to](), [install](), [linux](), [mongodb](), [tutorial](), [ubuntu]() ### AI overview A beginner-focused tutorial explains how to install MongoDB Community Edition on Ubuntu using the package manager. It covers importing MongoDB's GPG key, adding the package list, refreshing packages, and installing MongoDB, with notes about MongoDB 8.X and compatibility between Ubuntu versions. ### Source excerpt So you're ready to dabble with MongoDB on Linux and you've chosen Ubuntu as the variant you want to work with. Fantastic choice because you're in for a fairly easy experience that will get you up and ... The post How to Install MongoDB on Ubuntu: A Step-by-Step Guide for Beginners appeared first on DataCamp. ## How MongoDB Atlas Built a Predictive Auto-Scaler DevFeed: [How MongoDB Atlas Built a Predictive Auto-Scaler]() Original publisher: [Read original article]() Author: Byte-Sized Design Published: 2026-06-01T06:07:00Z Content type: article Language: en Sources: [Byte-Sized Design]() Topics: [MongoDB](), [cloud-infrastructure](), [Server]() Tags: [atlas](), [mongodb](), [servers]() ### AI overview The article describes how MongoDB Atlas built a predictive auto-scaler designed to scale infrastructure before server capacity becomes a problem. ### Source excerpt How Atlas built a predictive auto-scaler that scales before your servers break a sweat ## Running MongoDB in Docker - A Complete Guide with Examples DevFeed: [Running MongoDB in Docker - A Complete Guide with Examples]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-05-29T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [Docker](), [Docker Compose](), [Docker Container](), [Deployment](), [Docker Image](), [Authentication](), [Command-line interface]() Tags: [authentication](), [command-line](), [deployment](), [docker](), [docker-container](), [docker-image](), [examples](), [guide](), [linux](), [macos](), [mongodb](), [rancher](), [tutorial](), [windows]() ### AI overview A practical tutorial on deploying MongoDB with Docker for local or self-hosted use. It covers prerequisites, downloading official MongoDB Community Edition images, running MongoDB in an isolated container, port mapping, authentication configuration, and safer handling of sensitive information. ### Source excerpt So you're looking to self-host MongoDB or start dabbling with it in a local setting? There are a few options to get started if you don't want to jump directly into MongoDB Atlas, one of those options ... The post Running MongoDB in Docker - A Complete Guide with Examples appeared first on DataCamp. ## How to Design Nested Documents for a Blogging App DevFeed: [How to Design Nested Documents for a Blogging App]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-05-22T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [NoSQL](), [data-modeling](), [Content Management System]() Tags: [cms](), [data-modeling](), [database](), [how-to](), [mongodb](), [nosql]() ### AI overview A tutorial on designing nested documents for a blogging application in MongoDB. It examines document modeling choices for authors, blog posts, and comments, and explains why modeling these relationships as separate documents may not provide the best MongoDB experience. ### Source excerpt So you want to build your own content management system (CMS), also sometimes known as a blog? This is a classic example when learning how to use a database, whether it be a relational database manage... The post How to Design Nested Documents for a Blogging App appeared first on DataCamp. ## MongoDB and GraphQL: A Perfect Match DevFeed: [MongoDB and GraphQL: A Perfect Match]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-05-15T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [GraphQL](), [MongoDB](), [Tutorial](), [API](), [TypeScript](), [Node.js](), [Express]() Tags: [api](), [data](), [database](), [express](), [graphql](), [mongodb](), [node-js](), [tutorial](), [typescript]() ### AI overview This tutorial explains how to build a GraphQL API with MongoDB using TypeScript. It covers the consistent JSON-like data flow between GraphQL queries, the application, and MongoDB, and lists prerequisites including MongoDB Atlas, Node.js 22+, and the MongoDB Node.js Driver 6.x. ### Source excerpt GraphQL is a powerful and efficient way to build APIs. The client queries the API, similarly to how they would a database, and that API returns only the data that they've requested, often reducing the... The post MongoDB and GraphQL: A Perfect Match appeared first on DataCamp. ## Building a REST API With Express Framework and MongoDB DevFeed: [Building a REST API With Express Framework and MongoDB]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-05-08T12:00:00Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [Express](), [MongoDB](), [REST API](), [Tutorial](), [Node.js](), [JavaScript](), [Cross-origin resource sharing (CORS)](), [.env](), [JSON]() Tags: [api](), [code](), [cors](), [database](), [development](), [express](), [javascript](), [json](), [mongodb](), [node-js](), [nosql](), [rest](), [rest-api](), [tutorial]() ### AI overview A tutorial on building a REST API with Express Framework, MongoDB, and Node.js. It explains how JSON flows between clients, application logic, and MongoDB, then covers prerequisites, dependencies, CORS, environment configuration, and project structure. ### Source excerpt Almost every modern web application will need a REST API for the frontend to communicate with, and in almost every scenario, that frontend is going to expect to work with JSON data. As a result, the b... The post Building a REST API With Express Framework and MongoDB appeared first on Hevo. ## PCPJack | Cloud Worm Evicts TeamPCP and Steals Credentials at Scale DevFeed: [PCPJack | Cloud Worm Evicts TeamPCP and Steals Credentials at Scale]() Original publisher: [Read original article]() Author: Alex Delamotte Published: 2026-05-07T10:00:17Z Content type: article Language: en Sources: [SentinelLabs - We are hunters, reversers, exploit developers, and tinkerers shedding light on the world of malware, exploits, APTs, and cybercrime across all platforms.]() Topics: [pcpjack](), [Credential theft](), [Malware](), [cloud-infrastructure](), [Security](), [Docker](), [Kubernetes](), [web applications](), [MongoDB](), [Redis](), [VirusTotal](), [ransomware]() Tags: [cloud](), [credential-theft](), [database](), [docker](), [kubernetes](), [malware](), [open-source](), [pcpjack](), [ransomware](), [redis](), [security](), [teampcp](), [virustotal](), [web-applications]() ### AI overview SentinelLABS describes PCPJack as a credential-theft framework that spreads across exposed cloud infrastructure, removes TeamPCP-related artifacts, harvests credentials from cloud, container, developer, productivity, and financial services, and exfiltrates the data. The framework targets services including Docker, Kubernetes, Redis, MongoDB, and vulnerable web applications, with suspected monetization through fraud, spam, extortion, or resale of stolen access rather than cryptomining. ### Source excerpt Cloud attack framework skips cryptomining, harvests financial, messaging, and enterprise credentials for fraud, spam, and potential extortion. ## Using Dot Notation to Query Nested Fields in MongoDB DevFeed: [Using Dot Notation to Query Nested Fields in MongoDB]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-04-28T20:29:24Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [Tutorial](), [Query (disambiguation)](), [Database]() Tags: [arrays](), [collection](), [database](), [filter](), [mongodb](), [object](), [tutorial]() ### AI overview This tutorial explains how to use MongoDB dot notation to query and filter nested fields in documents, including fields within nested objects and arrays. ### Source excerpt If you're just starting to dabble with MongoDB, you've probably come to a point where your documents are looking a little complex. These documents might have gone from flat, relational-looking pieces ... The post Using Dot Notation to Query Nested Fields in MongoDB appeared first on DataCamp. ## Decoupling Authorization at Scale: MongoDB Atlas and Cedar-Based Resource Policies DevFeed: [Decoupling Authorization at Scale: MongoDB Atlas and Cedar-Based Resource Policies]() Original publisher: [Read original article]() Author: Sergio Ariel de la Campa Published: 2026-04-23T15:49:59Z Content type: article Language: en Sources: [AWS Open Source Blog]() Topics: [Authorization](), [MongoDB](), [Security](), [Architecture & Design](), [Provisioning](), [Software as a service](), [Amazon Web Services]() Tags: [database](), [enterprise](), [infrastructure](), [open-source](), [policy](), [saas](), [security]() ### AI overview The article explains how MongoDB Atlas uses Cedar-based resource policies to decouple authorization logic from application code. It discusses role- and attribute-based access control, policy verification, centralized governance, and enforcement across multi-tenant database deployments and cloud providers. ### Source excerpt As organizations scale applications, managing authorization becomes increasingly complex. What starts as role-based permissions quickly evolves into intricate rules spanning multiple services, regions, and compliance requirements. Traditional approaches of embedding authorization logic in application code lead to fragmented policies scattered across codebases, making them difficult to maintain, audit, and scale. These challenges have become more [...] ## The Inference Cloud Memory Layer: A Technical Dive into DigitalOcean Managed Databases DevFeed: [The Inference Cloud Memory Layer: A Technical Dive into DigitalOcean Managed Databases]() Original publisher: [Read original article]() Author: Joe Keegan Published: 2026-04-17T20:10:00Z Content type: article Language: en Sources: [DigitalOcean]() Topics: [Digital Ocean](), [Inference](), [Databases](), [Cloud](), [Artificial Intelligence](), [MongoDB](), [PostgreSQL](), [valkey]() Tags: [agent](), [agentic](), [ai](), [cloud](), [cloud-platform](), [databases](), [digitalocean](), [engineering](), [inference](), [mongodb](), [platform](), [postgresql](), [stateful](), [valkey]() ### AI overview This technical article presents DigitalOcean Managed Databases as the memory layer for an inference cloud. It explains how PostgreSQL, MongoDB, and Valkey can serve as systems of record for stateful AI applications, supporting persistent context, recovery in multi-stage workflows, and access to organization-specific data. ### Source excerpt As AI moves from experimental chat interfaces to production-grade agents, the need for a foundational memory layer to transform these AI-powered tasks into stateful models is apparent. The absence of a robust memory layer causes agents to lose vital statefulness, leading to: Inability to maintain long-term recall. Without persistent memory to track context across sessions, an agent might recognize specific user preferences in January but fail to apply that data months later, requiring the user to repeat the entire briefing. Vulnerability in multi-stage workflows. Lacking durable execution, there is no "save point" for recovery; consequently, a simple network interruption forces complex agentic processes, such as gathering diagnostic data via multiple tool calls, to restart entirely rather than resume from the point of failure. Disconnect from business-specific realities. If an agent cannot access private internal records or real-time operational data, it relies on general training data and guesswork, often confidently fabricating generic policies or specifications that are factually inaccurate for your organization. DigitalOcean is constantly evolving to meet this challenge, and we've entered the era of the inference cloud: A full-stack cloud platform purpose-built to run AI in production. With Gradient™AI Platform providing the specialized compute for AI applications, DigitalOcean Managed Databases serves as the foundational memory layer. Offerings from PostgreSQL, MongoDB, and Valkey function as the system of record for today's stateful AI applications, particularly so when they're connected to the DigitalOcean Agentic Inference Cloud. What is the inference cloud? The need for an inference cloud stems from a fundamental shift in how AI is being built, deployed, and used in 2026. For years, the industry's focus was on training or the capital-intensive process of building a model. But now developers are shifting to running that pre-trained model in a live product. T ## Build a Movie Watchlist with Node.js, TypeScript, and MongoDB DevFeed: [Build a Movie Watchlist with Node.js, TypeScript, and MongoDB]() Original publisher: [Read original article]() Author: Nic Raboy Published: 2026-04-13T13:37:28Z Content type: tutorial Language: en Sources: [Nic Raboy]() Topics: [MongoDB](), [Node.js](), [TypeScript](), [Express](), [REST API](), [API](), [Development](), [web applications]() Tags: [api](), [configuration](), [express](), [how-to](), [javascript](), [json](), [mongodb](), [node-js](), [nosql](), [rest-api](), [tutorial](), [typescript]() ### AI overview A tutorial that builds a small movie watchlist REST API with Node.js, TypeScript, Express, and MongoDB. It covers project setup, prerequisites, schema design, MongoDB Search for full-text search, configuration, and development commands. ### Source excerpt Almost every modern web application will need a REST API for a client to talk to, and in almost every scenario, that client is going to expect JSON. The best developer experience is a stack where you ... The post Build a Movie Watchlist with Node.js, TypeScript, and MongoDB appeared first on DEV. ## Pagination at Scale: Why OFFSET and SKIP Will Eventually Break Your API DevFeed: [Pagination at Scale: Why OFFSET and SKIP Will Eventually Break Your API]() Original publisher: [Read original article]() Author: hello@ankit-rana.com Published: 2026-03-17T00:00:00Z Content type: tutorial Language: en Sources: [Ankit Rana | Mechanical Sympathy]() Topics: [API](), [Database](), [MongoDB]() Tags: [api](), [api-design](), [b-tree](), [cursor](), [database-performance](), [latency](), [mongodb](), [pagination](), [scalability](), [scale](), [sql]() ### AI overview This article explains why OFFSET and SKIP pagination become slower and more memory-intensive as page depth increases. It presents cursor-based, or keyset, pagination as an alternative that uses an indexed range seek and reads a fixed number of rows, keeping fetch cost largely constant with list depth. The trade-off is that cursor pagination does not provide reliable absolute page numbers. ### Source excerpt OFFSET does not seek. The engine fetches offset plus limit rows, sorts them, and discards the first N, so cost grows linearly with page depth. Cursor pagination passes the last seen key instead of a page number, letting the B+ tree seek in logarithmic time and read a fixed number of rows, which keeps latency flat at any depth. The price is losing absolute page numbers. ## How MongoDB Stores Data - WiredTiger Pages vs SQLite DevFeed: [How MongoDB Stores Data - WiredTiger Pages vs SQLite]() Original publisher: [Read original article]() Published: 2026-03-09T00:00:00Z Content type: tutorial Language: en Sources: [Gaurav Sarma's Blog]() Topics: [MongoDB](), [SQLite](), [Databases](), [Data structures](), [Cache]() Tags: [cache](), [data-structures](), [database](), [memory](), [mongodb](), [performance](), [sqlite]() ### AI overview This tutorial explains how MongoDB's WiredTiger storage engine stores collection and index data in variable-size B-trees, then compares that model with SQLite's fixed-page B-tree and overflow-page design. It focuses on how page management, overflow references, reconciliation, and cache pressure can affect query performance. ### Source excerpt . [MongoDB WiredTiger vs SQLite Storage](mongodb-wiredtiger-vs-sqlite-storage-cover... ## DigitalOcean Managed Databases: 2025 Releases and Updates DevFeed: [DigitalOcean Managed Databases: 2025 Releases and Updates]() Original publisher: [Read original article]() Author: Nicole Ghalwash Published: 2025-12-17T16:37:44Z Content type: article Language: en Sources: [DigitalOcean]() Topics: [Databases](), [Digital Ocean](), [releases](), [observability](), [Scalability](), [valkey](), [MongoDB](), [MySQL](), [Kafka]() Tags: [2025](), [databases](), [digitalocean](), [kafka](), [mongodb](), [mysql](), [observability](), [releases](), [scalability](), [valkey]() ### AI overview A recap of DigitalOcean Managed Databases releases in 2025, covering database engine updates, increased storage limits, Valkey caching, MongoDB access controls, observability and hardening improvements, Kafka Schema Registry support, and an MCP Server for managing cloud resources through natural-language commands. ### Source excerpt 2025 was a big year for DigitalOcean Managed Databases, packed with meaningful enhancements designed to deliver more power, flexibility, and simplicity for developers and businesses of all sizes. With performance boosts and new database engines introduced to improve scalability, automation, and observability, this year's releases focused on making it easier than ever to build and run reliable data-backed applications on DigitalOcean. In this recap, we'll walk through the most impactful launches in both the first and second half of the year and how they help teams move faster while keeping complexity low. First, let's take a look at our releases in the first half of the year (H1): - Managed PostgreSQL support for v17 [February] - Managed MongoDB support for v8 [March] - Support for up to 20TB for Managed MySQL and 30TB for PostgreSQL [March] - Introducing DigitalOcean Managed Caching for Valkey [April] - Introducing Role-Based Access Control to DigitalOcean Managed MongoDB with Predefined Roles [May] - Database Observability, Monitoring, and Hardening Advancements [June] - Support for Kafka Schema Registry [July] The second half (H2) of 2025 saw even more big developments for DigitalOcean Managed Databases: MCP Server (August) The DigitalOcean MCP (Model Context Protocol) Server lets you manage your cloud resources using simple, natural-language commands through AI-powered tools like Cursor, Claude, or your own custom LLMs. Running locally, it streamlines tasks such as provisioning Managed Databases, making cloud operations faster, easier, and more intuitive for developers. DigitalOcean MCP Server marks a major step forward in bringing AI directly into cloud infrastructure workflows. It allows users to seamlessly integrate cloud management into AI assistants or custom-built agents while eliminating context switching, manual API calls, and constant console navigation. MCP Servers make managing cloud infrastructure with LLMs faster, more secure, and far more accessible [Next page]()