Click Below to Get the Code

Browse, clone, and build from real-world templates powered by Harper.
News
GitHub Logo

Introducing HarperDB 4.1: Faster, More Efficient, & More Control

HarperDB 4.1 is released with new features: worker threads for HTTP requests, session affinity for routing, improved NoSQL query handling, flexible storage configuration, streamlined logging, and cluster networking.
Product Update
News
Product Update

Introducing HarperDB 4.1: Faster, More Efficient, & More Control

Harper
at Harper
April 17, 2023
Harper
at Harper
April 17, 2023
Harper
at Harper
April 17, 2023
April 17, 2023
HarperDB 4.1 is released with new features: worker threads for HTTP requests, session affinity for routing, improved NoSQL query handling, flexible storage configuration, streamlined logging, and cluster networking.
Harper

HarperDB 4.1 Has Arrived

We are excited to announce the release of HarperDB 4.1, packed with new features and enhancements that further elevate your HarperDB experience. This latest version brings cutting-edge improvements to concurrency handling, routing functionality, NoSQL query performance, storage configuration, logging, cluster networking, and integration with AWS S3 services. Let's delve into the details and explore the real-world value that HarperDB 4.1 delivers:

Click Here for HarperDB 4.1 Release Notes

Update Overview

Concurrency Handling with Worker Thread

HarperDB 4.1 introduces worker threads for handling HTTP requests, providing significant benefits in traffic delegation, load tracking, session affinity, debuggability, and memory footprint reduction. Start HarperDB within your IDE, set breakpoints in your custom functions, and debug them seamlessly. For example, you can now debug custom functions if you're running HarperDB locally and using a modern IDE like WebStorm or VSCode.

Enhanced Routing with Session Affinity

The associated routing functionality in HarperDB 4.1 includes session affinity support. This feature enables consistent routing of users to the same thread, improving caching locality, performance, and fairness. By enabling session affinity with http.sessionAffinity, you can ensure users are consistently served by the same thread, providing a personalized user experience.

Revamped NoSQL Query Handling with Iterators

HarperDB 4.1 improves NoSQL query handling by utilizing iterators consistently. This approach offers an incredibly memory-efficient mechanism for streaming query results directly to the network as they are computed. The benefits are two-fold: faster Time to First Byte (TTFB), allowing data to be sent before the entire query is computed, and reduced memory usage during querying. This upgrade enables seamless and efficient access to query results, even within custom functions. Developers can leverage iterators to iteratively access data from the database without loading the entire result set into memory. Enjoy faster response times and more efficient resource utilization with this transparent upgrade.

Flexible Storage Configuration

HarperDB 4.1 introduces configuration options that allow you to specify the location of database storage files. This flexibility empowers you to distribute database directories and files across different volumes, optimizing disk utilization and storage performance. This feature will align your storage infrastructure with your specific requirements and achieve better scalability, resilience, and efficiency.

Streamlined Logging

Logging in HarperDB has been revamped and consolidated into a single hdb.log file in response to user feedback. This enhancement simplifies log management, making monitoring and analyzing system activity easier. The updated logging system gives you better insights into your HarperDB deployment, enabling you to diagnose issues and troubleshoot more effectively.

Cluster Networking with cluster_network Operation

The new cluster_network operation in HarperDB 4.1 allows you to ping the cluster and retrieve a list of enmeshed nodes. This feature enhances visibility and monitoring within a clustered environment, empowering you to monitor the health and connectivity of your HarperDB cluster effortlessly.

HarperDB 4.1 Has Arrived

We are excited to announce the release of HarperDB 4.1, packed with new features and enhancements that further elevate your HarperDB experience. This latest version brings cutting-edge improvements to concurrency handling, routing functionality, NoSQL query performance, storage configuration, logging, cluster networking, and integration with AWS S3 services. Let's delve into the details and explore the real-world value that HarperDB 4.1 delivers:

Click Here for HarperDB 4.1 Release Notes

Update Overview

Concurrency Handling with Worker Thread

HarperDB 4.1 introduces worker threads for handling HTTP requests, providing significant benefits in traffic delegation, load tracking, session affinity, debuggability, and memory footprint reduction. Start HarperDB within your IDE, set breakpoints in your custom functions, and debug them seamlessly. For example, you can now debug custom functions if you're running HarperDB locally and using a modern IDE like WebStorm or VSCode.

Enhanced Routing with Session Affinity

The associated routing functionality in HarperDB 4.1 includes session affinity support. This feature enables consistent routing of users to the same thread, improving caching locality, performance, and fairness. By enabling session affinity with http.sessionAffinity, you can ensure users are consistently served by the same thread, providing a personalized user experience.

Revamped NoSQL Query Handling with Iterators

HarperDB 4.1 improves NoSQL query handling by utilizing iterators consistently. This approach offers an incredibly memory-efficient mechanism for streaming query results directly to the network as they are computed. The benefits are two-fold: faster Time to First Byte (TTFB), allowing data to be sent before the entire query is computed, and reduced memory usage during querying. This upgrade enables seamless and efficient access to query results, even within custom functions. Developers can leverage iterators to iteratively access data from the database without loading the entire result set into memory. Enjoy faster response times and more efficient resource utilization with this transparent upgrade.

Flexible Storage Configuration

HarperDB 4.1 introduces configuration options that allow you to specify the location of database storage files. This flexibility empowers you to distribute database directories and files across different volumes, optimizing disk utilization and storage performance. This feature will align your storage infrastructure with your specific requirements and achieve better scalability, resilience, and efficiency.

Streamlined Logging

Logging in HarperDB has been revamped and consolidated into a single hdb.log file in response to user feedback. This enhancement simplifies log management, making monitoring and analyzing system activity easier. The updated logging system gives you better insights into your HarperDB deployment, enabling you to diagnose issues and troubleshoot more effectively.

Cluster Networking with cluster_network Operation

The new cluster_network operation in HarperDB 4.1 allows you to ping the cluster and retrieve a list of enmeshed nodes. This feature enhances visibility and monitoring within a clustered environment, empowering you to monitor the health and connectivity of your HarperDB cluster effortlessly.

HarperDB 4.1 is released with new features: worker threads for HTTP requests, session affinity for routing, improved NoSQL query handling, flexible storage configuration, streamlined logging, and cluster networking.

Download

White arrow pointing right
HarperDB 4.1 is released with new features: worker threads for HTTP requests, session affinity for routing, improved NoSQL query handling, flexible storage configuration, streamlined logging, and cluster networking.

Download

White arrow pointing right
HarperDB 4.1 is released with new features: worker threads for HTTP requests, session affinity for routing, improved NoSQL query handling, flexible storage configuration, streamlined logging, and cluster networking.

Download

White arrow pointing right

Explore Recent Resources

Blog
GitHub Logo

5 Architectures for Web Personalization

Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.
Blog
Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.
Person with short dark hair and moustache, wearing a colorful plaid shirt, smiling outdoors in a forested mountain landscape.
Aleks Haugom
Senior Manager of GTM
Blog

5 Architectures for Web Personalization

Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.
Aleks Haugom
Jul 2026
Blog

5 Architectures for Web Personalization

Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.
Aleks Haugom
Blog

5 Architectures for Web Personalization

Personalization is a data-delivery problem. Every architectural choice reduces to two distances: compute to user, and compute to fresh data. This piece maps five real architectures against both axes, scored on a concrete retailer workload where stale or slow data breaks the business.
Aleks Haugom
Blog
GitHub Logo

Agentic Engineering Needs an Opinion: Why Scale Starts with Architecture

AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.
Select*
Blog
AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.
A smiling man with a beard and salt-and-pepper hair stands outdoors with arms crossed, wearing a white button-down shirt.
Stephen Goldberg
CEO & Co-Founder
Blog

Agentic Engineering Needs an Opinion: Why Scale Starts with Architecture

AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.
Stephen Goldberg
Jun 2026
Blog

Agentic Engineering Needs an Opinion: Why Scale Starts with Architecture

AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.
Stephen Goldberg
Blog

Agentic Engineering Needs an Opinion: Why Scale Starts with Architecture

AI coding works in a sandbox because the environment is trivially narrow. Real systems have history, constraints, and blast radius. Coding agents make sound decisions only when the architecture is explicit and shared. Opinion isn't a constraint on agentic engineering, it's what makes it possible at scale.
Stephen Goldberg
Blog
GitHub Logo

Building a Cozy Sandbox Game on Harper

A nature-restoration game with six biomes, 150 animals, and a real food web — built with a single Harper component as the entire backend. One YAML file wires the database, API, content seeder, and static host. The same binary ships offline on itch.io.
Shell
Blog
A nature-restoration game with six biomes, 150 animals, and a real food web — built with a single Harper component as the entire backend. One YAML file wires the database, API, content seeder, and static host. The same binary ships offline on itch.io.
Person with long wavy brown hair wearing a bright pink shirt with a teal trim, smiling outdoors in soft sunlight with blurred trees in the background.
Bailey Dunning
Forward Deployed Engineer
Blog

Building a Cozy Sandbox Game on Harper

A nature-restoration game with six biomes, 150 animals, and a real food web — built with a single Harper component as the entire backend. One YAML file wires the database, API, content seeder, and static host. The same binary ships offline on itch.io.
Bailey Dunning
Jun 2026
Blog

Building a Cozy Sandbox Game on Harper

A nature-restoration game with six biomes, 150 animals, and a real food web — built with a single Harper component as the entire backend. One YAML file wires the database, API, content seeder, and static host. The same binary ships offline on itch.io.
Bailey Dunning
Blog

Building a Cozy Sandbox Game on Harper

A nature-restoration game with six biomes, 150 animals, and a real food web — built with a single Harper component as the entire backend. One YAML file wires the database, API, content seeder, and static host. The same binary ships offline on itch.io.
Bailey Dunning
Blog
GitHub Logo

Your Website was Built for Humans. AI Needs Something Cleaner.

The web spent a decade optimizing for browsers. JavaScript-heavy rendering, dynamic CMS templates, and client-side hydration made pages beautiful and machines blind. AI answer engines retrieve, parse, and cite content directly. If your best content is trapped behind a render cycle, a cleaner source wins.
A.I.
Blog
The web spent a decade optimizing for browsers. JavaScript-heavy rendering, dynamic CMS templates, and client-side hydration made pages beautiful and machines blind. AI answer engines retrieve, parse, and cite content directly. If your best content is trapped behind a render cycle, a cleaner source wins.
Person with short dark hair and moustache, wearing a colorful plaid shirt, smiling outdoors in a forested mountain landscape.
Aleks Haugom
Senior Manager of GTM
Blog

Your Website was Built for Humans. AI Needs Something Cleaner.

The web spent a decade optimizing for browsers. JavaScript-heavy rendering, dynamic CMS templates, and client-side hydration made pages beautiful and machines blind. AI answer engines retrieve, parse, and cite content directly. If your best content is trapped behind a render cycle, a cleaner source wins.
Aleks Haugom
Jun 2026
Blog

Your Website was Built for Humans. AI Needs Something Cleaner.

The web spent a decade optimizing for browsers. JavaScript-heavy rendering, dynamic CMS templates, and client-side hydration made pages beautiful and machines blind. AI answer engines retrieve, parse, and cite content directly. If your best content is trapped behind a render cycle, a cleaner source wins.
Aleks Haugom
Blog

Your Website was Built for Humans. AI Needs Something Cleaner.

The web spent a decade optimizing for browsers. JavaScript-heavy rendering, dynamic CMS templates, and client-side hydration made pages beautiful and machines blind. AI answer engines retrieve, parse, and cite content directly. If your best content is trapped behind a render cycle, a cleaner source wins.
Aleks Haugom