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Commerce Without Latency: How to Build Backends with Sub-millisecond Responses

Learn how top retailers achieve sub-millisecond response times by unifying backend systems. Cut latency, boost revenue, and scale effortlessly with simplified architecture and real-world results.
Blog

Commerce Without Latency: How to Build Backends with Sub-millisecond Responses

Jaxon Repp
Field CTO
at Harper
December 9, 2024
Jaxon Repp
Field CTO
at Harper
December 9, 2024
Jaxon Repp
Field CTO
at Harper
December 9, 2024
December 9, 2024
Learn how top retailers achieve sub-millisecond response times by unifying backend systems. Cut latency, boost revenue, and scale effortlessly with simplified architecture and real-world results.
Jaxon Repp
Field CTO

Your slow page load just cost you a sale.

For major retail sites, backend performance has a direct impact on revenue. Database queries that take over 150 milliseconds and page builds that take triple that result in lost sales and frustrated customers.

Leading retailers are solving this challenge with a revolutionary approach to platform efficiency– eliminating the traditional separation between database, cache, and application interfaces- reducing roundtrip response times from over 500ms to less than 25ms, even at a massive scale. Customers with optimized production deployments- regularly delivering millions of product pages overseeing terabytes of data- have seen no degradation in performance, even during peak holiday events.

The Scale of Complexity and The Complexity of Scale

Traditional enterprise architectures often look like this:

  • RDBMS and Document Databases for data storage
  • Redis for caching
  • Kafka for messaging
  • Multiple application servers
  • Load balancers between each layer

Each system requires its own infrastructure, maintenance, and specialized expertise. More importantly, the connections between these systems add latency. Here's what happens when a customer requests a product page:

  • Your application server has to query the database
  • Data must be serialized and deserialized between systems
  • Results often need to be cached in Redis
  • Each network hop adds delay
  • Any system hitting capacity can become a bottleneck

At scale, this complexity compounds. Engineering teams spend more time managing infrastructure than building features. Performance optimizations require coordinating changes across multiple systems. Even simple updates risk disrupting the delicate balance between services.

Simplifying Scale with A Unified Architecture

Harper takes a fundamentally different approach. Instead of connecting multiple specialized systems, we've combined database, cache, application, and messaging interfaces in a single binary. The benefits are substantial:

  • Database queries that took over 150ms now complete in under one millisecond
  • No more network hops between services
  • No serialization/deserialization overhead
  • Dramatically simplified infrastructure
  • Consistently fast performance scaled to billions of records and trillions of requests

Major retailers use this approach to serve massive product catalogs with sub-millisecond server response times. The simplified architecture is not only faster, but it's also easier to deploy, maintain, monitor, and scale.

Accelerating Page Loads with Full-Page Caching

Traditional CDNs cache static content, but dynamic data still requires expensive round trips to origin databases. Harper takes a different approach—distributing your applications and their underlying data across a mesh-networked cluster of application delivery engines. These can be flexibly deployed geographically and scaled infinitely as your users' access patterns evolve.

We built a platform inspired by the best cloud applications and edge performance platforms—the kind of system we'd want to use ourselves if we had unlimited budget and time. While the low-code movement had faded, its legacy left behind complex, unwieldy systems. As four experienced technical co-founders, we each took ownership of one part of our core product suite. Though we had intense debates and disagreements, we ultimately found common ground. Most importantly, the benchmarks validated our decisions.

One of our core strengths was the ability to deliver any data, in any format, and of any size—with remarkable speed. We identified modern retail as our most sophisticated target market. With its personalized experiences and billions of transactions—each tied to individual users across multiple third parties—top performers in this space can translate a 50% reduction in latency into millions of dollars in revenue.

Our team built the first project, and Harper quickly gained internal champions. We made ourselves available around the clock to help optimize architectures and infrastructure. When asked if we could handle full-page caching and personalization at the edge at scale, we smiled—this was exactly the trust we needed to earn.

Our opportunity came with one of the world's largest retailers heading into the holiday season. They had already built the application, and its performance seemed almost too good to be true. We made a few tweaks and provided advice when asked.

But more importantly, we solved one of the biggest challenges facing a developer-driven platform: the learning curve had to justify the switching costs. It needed to be easy but not limiting. While everyone thinks their creation is special, having another development shop working at massive scale validated that our solution was elegant, simple, fast, and cost-effective from day one. This confirmed our vision—collapsing the stack truly was the next breakthrough in global data performance.

How It Works

When a request comes in, Harper either serves the response directly from RAM cache, or makes a near-instant lookup from the local disk, or multiple attached storage volumes. There are no network requests, no drivers, no external services necessary. The platform handles all the complexities of your application, storage, and messaging locally. Our highly-configurable replication engine means you can tailor your sharding algorithm with a few lines of code, and any network outages can heal after things come back online.

This architecture has been proven to reliably handle hundreds of millions of product pages for large-scale commerce sites while maintaining sub-millisecond response times.

Ready to get started? Grab our full-page caching component from GitHub and see the performance difference for yourself.

Real World Results

Major e-commerce companies implementing Harper have seen dramatic improvements in search engine rankings and page load performance. Our simple but effective platform crushed it during Black Friday and Cyber Monday without a hiccup. We meticulously examined the logs for any issues, bottlenecks, or underperformance—but found none. The platform's stability during peak traffic periods drove such substantial revenue increases that we knew we'd achieved our goal: creating a system that makes it easy to innovate and scale from proof of concept to production and beyond to what we call "Ludicrous Speed." Better yet, our customer saw immediate improvements in their Google search rankings for product pages.

Getting Started

Start your performance optimization journey today by checking out our full documentation, reaching out to our team, or following these steps:

  1. Sign up for a free Harper account
  2. Install Harper locally for free and manage it through Harper Fabric
  3. Deploy a free Fabric cluster to test the platform's performance and reliability
  4. Import your data through our simple REST API or other native interfaces: GraphQL, MQTT, WebSocket, and Server-Sent Events
  5. Install our full-page caching component
  6. Measure the performance difference

Our team is ready to help with questions and implementation guidance. Having helped some of the world's largest retailers optimize their performance, we're confident we can help you achieve similar results.

Your slow page load just cost you a sale.

For major retail sites, backend performance has a direct impact on revenue. Database queries that take over 150 milliseconds and page builds that take triple that result in lost sales and frustrated customers.

Leading retailers are solving this challenge with a revolutionary approach to platform efficiency– eliminating the traditional separation between database, cache, and application interfaces- reducing roundtrip response times from over 500ms to less than 25ms, even at a massive scale. Customers with optimized production deployments- regularly delivering millions of product pages overseeing terabytes of data- have seen no degradation in performance, even during peak holiday events.

The Scale of Complexity and The Complexity of Scale

Traditional enterprise architectures often look like this:

  • RDBMS and Document Databases for data storage
  • Redis for caching
  • Kafka for messaging
  • Multiple application servers
  • Load balancers between each layer

Each system requires its own infrastructure, maintenance, and specialized expertise. More importantly, the connections between these systems add latency. Here's what happens when a customer requests a product page:

  • Your application server has to query the database
  • Data must be serialized and deserialized between systems
  • Results often need to be cached in Redis
  • Each network hop adds delay
  • Any system hitting capacity can become a bottleneck

At scale, this complexity compounds. Engineering teams spend more time managing infrastructure than building features. Performance optimizations require coordinating changes across multiple systems. Even simple updates risk disrupting the delicate balance between services.

Simplifying Scale with A Unified Architecture

Harper takes a fundamentally different approach. Instead of connecting multiple specialized systems, we've combined database, cache, application, and messaging interfaces in a single binary. The benefits are substantial:

  • Database queries that took over 150ms now complete in under one millisecond
  • No more network hops between services
  • No serialization/deserialization overhead
  • Dramatically simplified infrastructure
  • Consistently fast performance scaled to billions of records and trillions of requests

Major retailers use this approach to serve massive product catalogs with sub-millisecond server response times. The simplified architecture is not only faster, but it's also easier to deploy, maintain, monitor, and scale.

Accelerating Page Loads with Full-Page Caching

Traditional CDNs cache static content, but dynamic data still requires expensive round trips to origin databases. Harper takes a different approach—distributing your applications and their underlying data across a mesh-networked cluster of application delivery engines. These can be flexibly deployed geographically and scaled infinitely as your users' access patterns evolve.

We built a platform inspired by the best cloud applications and edge performance platforms—the kind of system we'd want to use ourselves if we had unlimited budget and time. While the low-code movement had faded, its legacy left behind complex, unwieldy systems. As four experienced technical co-founders, we each took ownership of one part of our core product suite. Though we had intense debates and disagreements, we ultimately found common ground. Most importantly, the benchmarks validated our decisions.

One of our core strengths was the ability to deliver any data, in any format, and of any size—with remarkable speed. We identified modern retail as our most sophisticated target market. With its personalized experiences and billions of transactions—each tied to individual users across multiple third parties—top performers in this space can translate a 50% reduction in latency into millions of dollars in revenue.

Our team built the first project, and Harper quickly gained internal champions. We made ourselves available around the clock to help optimize architectures and infrastructure. When asked if we could handle full-page caching and personalization at the edge at scale, we smiled—this was exactly the trust we needed to earn.

Our opportunity came with one of the world's largest retailers heading into the holiday season. They had already built the application, and its performance seemed almost too good to be true. We made a few tweaks and provided advice when asked.

But more importantly, we solved one of the biggest challenges facing a developer-driven platform: the learning curve had to justify the switching costs. It needed to be easy but not limiting. While everyone thinks their creation is special, having another development shop working at massive scale validated that our solution was elegant, simple, fast, and cost-effective from day one. This confirmed our vision—collapsing the stack truly was the next breakthrough in global data performance.

How It Works

When a request comes in, Harper either serves the response directly from RAM cache, or makes a near-instant lookup from the local disk, or multiple attached storage volumes. There are no network requests, no drivers, no external services necessary. The platform handles all the complexities of your application, storage, and messaging locally. Our highly-configurable replication engine means you can tailor your sharding algorithm with a few lines of code, and any network outages can heal after things come back online.

This architecture has been proven to reliably handle hundreds of millions of product pages for large-scale commerce sites while maintaining sub-millisecond response times.

Ready to get started? Grab our full-page caching component from GitHub and see the performance difference for yourself.

Real World Results

Major e-commerce companies implementing Harper have seen dramatic improvements in search engine rankings and page load performance. Our simple but effective platform crushed it during Black Friday and Cyber Monday without a hiccup. We meticulously examined the logs for any issues, bottlenecks, or underperformance—but found none. The platform's stability during peak traffic periods drove such substantial revenue increases that we knew we'd achieved our goal: creating a system that makes it easy to innovate and scale from proof of concept to production and beyond to what we call "Ludicrous Speed." Better yet, our customer saw immediate improvements in their Google search rankings for product pages.

Getting Started

Start your performance optimization journey today by checking out our full documentation, reaching out to our team, or following these steps:

  1. Sign up for a free Harper account
  2. Install Harper locally for free and manage it through Harper Fabric
  3. Deploy a free Fabric cluster to test the platform's performance and reliability
  4. Import your data through our simple REST API or other native interfaces: GraphQL, MQTT, WebSocket, and Server-Sent Events
  5. Install our full-page caching component
  6. Measure the performance difference

Our team is ready to help with questions and implementation guidance. Having helped some of the world's largest retailers optimize their performance, we're confident we can help you achieve similar results.

Learn how top retailers achieve sub-millisecond response times by unifying backend systems. Cut latency, boost revenue, and scale effortlessly with simplified architecture and real-world results.

Download

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Learn how top retailers achieve sub-millisecond response times by unifying backend systems. Cut latency, boost revenue, and scale effortlessly with simplified architecture and real-world results.

Download

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Learn how top retailers achieve sub-millisecond response times by unifying backend systems. Cut latency, boost revenue, and scale effortlessly with simplified architecture and real-world results.

Download

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