Everything You Need to Build Faster

Harper’s Early Hints solution accelerates web performance by sending critical assets to browsers using HTTP 103 responses before the full page loads, improving Core Web Vitals, SEO, and conversions. Built on Harper’s fused architecture, it delivers sub-2 ms latency at scale with zero changes to application code.

The blog highlights a key contradiction in AI-powered e-commerce: smarter experiences often come with slower performance. Centralized architectures introduce latency that hurts user experience and revenue, especially when milliseconds matter. To solve this, AI must run at the edge—where vector search, semantic caching, and product logic are co-located—delivering instant, relevant results without routing through distant servers. By fusing intelligence with speed, edge-native AI turns performance into a competitive advantage.

Harper 4.6 introduces native vector indexing (HNSW), developer-first logging, and a plugins API—boosting semantic search, debugging, and modularity, all with minimal performance impact. Ideal for AI-native apps and scaling with ease.

Harper announces the launch of its open-source Model Context Protocol (MCP) server, natively integrated into its data engine. This advancement delivers a high-performance, unified platform for LLM-native applications, enabling efficient, multi-modal context retrieval with minimal infrastructure overhead.

The post introduces Harper 4.6 and its new capabilities for semantic search at the edge, eliminating the need for separate vector stores and caches. It explains how this release simplifies AI-powered application stacks and boosts performance.

Harper 4.6 introduces vector indexing for AI-powered semantic search and caching, empowering brands to deliver faster, smarter digital experiences that boost engagement and drive conversions.

Discover how HarperDB's peer-to-peer data replication powers globally distributed, low-latency systems with no single point of failure. Learn to configure clusters, secure them with mTLS, and scale seamlessly using real-world examples and practical guides.

Discover what it really takes to self-host Next.js beyond just running next start. Learn how Harper reimagined the entire Next.js lifecycle. Develop, Build, Deploy, and Run, to support clustered, bare-metal environments with hot reload, rolling deploys, multi-zone support, and more.

Discover how event-driven database architecture unifies storage and real-time messaging. Harper’s MQTT topics make data updates instant and seamless.

This article is a holiday readiness guide for developers, offering practical tips to handle peak traffic and ensure fast, reliable shopping experiences. It highlights how Harper’s backend platform can optimize caching, search, personalization, and checkout while reducing infrastructure complexity and cost.

Harper revolutionizes GraphQL performance by fusing database, cache, application logic, and messaging into a single edge-native runtime—eliminating CDN cache misses, reducing backend strain, and slashing latency. With features like whole and partial query caching, real-time data freshness via CDC, and an incremental adoption path, Harper enables fast, scalable, and simplified GraphQL delivery without major rewrites.

Harper joins the OpenJS Foundation as a Silver Member, bringing its Node.js-powered composable application platform to the JavaScript community. With a focus on performance, open-source collaboration, and developer experience, Harper strengthens its commitment to advancing modern, distributed applications.

Harper is a high-performance backend platform that enhances both user and bot experiences with native pre-rendering, low-latency delivery, and resilient infrastructure. Unlike Botify, which focuses solely on SEO analytics and bot optimization, Harper empowers developers to improve Core Web Vitals and uptime directly at the infrastructure layer.

Harper enables normalized data to be a practical storage solution with minimal impact on read performance.

Harper Pre-render transforms modern websites into ultra-fast, SEO-friendly experiences by generating and caching HTML ahead of time. It eliminates the drawbacks of client-side rendering, ensuring instant page loads for users and fully indexable content for search engines—at scale and with minimal backend strain.

Discover how resource hints like preload, preconnect, and Early Hints can dramatically boost web performance. Learn how each hint impacts key metrics like LCP and TTFB, with practical examples and implementation strategies to speed up page load and enhance user experience.

Microliths are an emerging software architecture that combine the simplicity and performance of monoliths with the modularity and scalability of microservices, offering vertically integrated units where application logic, database, cache, and APIs coexist in a single deployable runtime. This approach enables ultra-low-latency, secure, and composable systems with significantly less code and operational overhead, making it ideal for modern, data-intensive applications.

This article explores how to build a scalable, secure multi-tenant asset management system using Harper's blob storage, using the platform's unique latency advantages.

AI-driven personalization of e-commerce product pages boosts conversions by tailoring content to customer cohorts, reducing purchase friction, and enhancing SEO—while remaining cost-effective via open-source models and smart deployment.

Redis is fast but adds operational complexity—requiring separate infrastructure, custom code, and ongoing maintenance. Harper eliminates this overhead with built-in, declarative caching, delivering performance, scalability, and simplicity in a single platform that handles both data and caching seamlessly.

Learn how to create a full Library Management System using Harper. Define GraphQL schemas, implement resource classes, and build APIs without boilerplate code.

On February 3, 2026, Microsoft will sunset support for Dynamics 365 Fraud Protection (DFP), prompting enterprises to evaluate new fraud prevention strategies. Akamai Account Protector (APR) continues to offer trusted device fingerprints and risk scores, but Azure Active Directory B2C (B2C) does not propagate APR’s risk score header downstream. Risk Query bridges this gap with a lightweight, distributed key-value service that enables APR to write and B2C to read, restoring fraud protection logic.

Harper’s Distributed Query Delivery solution moves APIs and the data they rely on to the edge, creating a multi‑protocol query delivery layer near every user. Streaming changes from your origin sources to distributed Harper nodes resolves queries at the edge instead of fanning out across microservices. This dramatically cuts latency and cloud costs, providing measurable improvements in performance, reliability, and total cost of ownership.