Up to 14× faster than Vercel on live data

Click Below to Get the Code

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

HarperDB 4.3 - CRDT Distributed Counter, Query Improvements, and Operational Enhancements

HarperDB 4.3 brings relational querying, decentralized counters, and secure connections for distributed applications and improved developer experience.

News

Product Update

HarperDB 4.3 - CRDT Distributed Counter, Query Improvements, and Operational Enhancements

Harper

at Harper

March 18, 2024

Harper

at Harper

March 18, 2024

Harper

at Harper

March 18, 2024

March 18, 2024

HarperDB 4.3 brings relational querying, decentralized counters, and secure connections for distributed applications and improved developer experience.

Harper

4.3 Has Arrived

We are stoked to introduce exciting new capabilities in our first release of 2024. With HarperDB 4.3, you can define data relationships to efficiently execute joins at scale, build decentralized counters, and work effectively in an air-gapped environment. This article will only discuss some of the major updates. Please see our 4.3 release notes for a complete list of changes and their technical details.

‍

Overview of Key Updates

CRDT Distributed Counter

With near-instant leaderless global data replication, HarperDB was already an excellent choice for building distributed applications. With 4.3, we have added conflict-free replicated data type (CRDT) incrementation, giving you even more power. This addition enables decentralized counting for use cases like globalized API throttling, real-time logistic operations, gaming leaderboards, and managing engagements on decentralized social media networks. Click here for our guide on CRDT in HarperDB.

Relationships & Joins

4.3 introduces deep relational querying for object-oriented data. This powerful new addition allows direct-from-client URL querying that bypasses most of the inefficiencies behind SQL queries in relation databases. For a complete understanding of this functionality, read this introductory guide from our SVP of Engineering.

mTLS Support

One common use case for HarperDB is integrating it with existing infrastructure to reduce origin load and significantly improve the user experience. To help ensure the HarperDB’s connection to existing infrastructure is secure, 4.3 includes support for tamper-resistant Mutual Transport Layer Security (mTLS).

Local Studio Upgrade

HarperDB’s web-based IDE, HarperDB Studio, is a favorite feature amongst developers. It lets engineers take advantage of HarperDB’s application engine without the complex setup that alternative databases require. With 4.3, engineers can build applications using the HarperDB Studio while offline. Click here for details on enabling this functionality.

‍

INDEX

White arrow pointing right

Read the Full Story

White arrow pointing right

No items found.

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Harper Named a Sample Vendor in the Gartner® Hype Cycle™ for Digital Commerce, 2026

Harper was named a 2026 Gartner Hype Cycle for Digital Commerce Sample Vendor, recognized in Front-End Cloud for its unified runtime combining data, application logic, messaging, and agent development together.

4.3 Has Arrived

We are stoked to introduce exciting new capabilities in our first release of 2024. With HarperDB 4.3, you can define data relationships to efficiently execute joins at scale, build decentralized counters, and work effectively in an air-gapped environment. This article will only discuss some of the major updates. Please see our 4.3 release notes for a complete list of changes and their technical details.

‍

Overview of Key Updates

CRDT Distributed Counter

With near-instant leaderless global data replication, HarperDB was already an excellent choice for building distributed applications. With 4.3, we have added conflict-free replicated data type (CRDT) incrementation, giving you even more power. This addition enables decentralized counting for use cases like globalized API throttling, real-time logistic operations, gaming leaderboards, and managing engagements on decentralized social media networks. Click here for our guide on CRDT in HarperDB.

Relationships & Joins

4.3 introduces deep relational querying for object-oriented data. This powerful new addition allows direct-from-client URL querying that bypasses most of the inefficiencies behind SQL queries in relation databases. For a complete understanding of this functionality, read this introductory guide from our SVP of Engineering.

mTLS Support

One common use case for HarperDB is integrating it with existing infrastructure to reduce origin load and significantly improve the user experience. To help ensure the HarperDB’s connection to existing infrastructure is secure, 4.3 includes support for tamper-resistant Mutual Transport Layer Security (mTLS).

Local Studio Upgrade

HarperDB’s web-based IDE, HarperDB Studio, is a favorite feature amongst developers. It lets engineers take advantage of HarperDB’s application engine without the complex setup that alternative databases require. With 4.3, engineers can build applications using the HarperDB Studio while offline. Click here for details on enabling this functionality.

‍

HarperDB 4.3 brings relational querying, decentralized counters, and secure connections for distributed applications and improved developer experience.

Download

White arrow pointing right

HarperDB 4.3 brings relational querying, decentralized counters, and secure connections for distributed applications and improved developer experience.

Download

White arrow pointing right

HarperDB 4.3 brings relational querying, decentralized counters, and secure connections for distributed applications and improved developer experience.

Download

White arrow pointing right

Explore Recent Resources

How to Reduce API Latency Under Load Without Adding Another Cache Tier

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

Blog

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

Austin Akers

Head of Developer Relations

How to Reduce API Latency Under Load Without Adding Another Cache Tier

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

How to Reduce API Latency Under Load Without Adding Another Cache Tier

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

How to Reduce API Latency Under Load Without Adding Another Cache Tier

Reduce API latency under load with a caching alternative to Redis: an in-process cache that cut response time 100x without adding a new tier.

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

News

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Aleks Haugom

Senior Manager of GTM

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

Harper 5.2: More Throughput per Node, Fewer Systems Around It

Harper 5.2 helps architecture and platform leaders improve performance, control infrastructure costs, secure production workloads, and reduce operational complexity by bringing faster data access, agentic capabilities, scheduling, backup, routing, and protection into one unified runtime.

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.

Aleks Haugom

Senior Manager of GTM

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.

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.

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.

5x Faster HNSW Vector Search with int8 Quantization

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

Tutorial

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

Kris Zyp

SVP of Engineering

5x Faster HNSW Vector Search with int8 Quantization

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

5x Faster HNSW Vector Search with int8 Quantization

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

5x Faster HNSW Vector Search with int8 Quantization

Harper 5.1 adds int8 quantization, dropping index size by roughly 3x, search throughput improves roughly 5x, and p99 latency falls from ~9s to ~0.5s under load. The tradeoff is approximately 1% recall degradation before reranking.

Vercel vs. Harper Benchmark Test

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

Comparison

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

Harper

Vercel vs. Harper Benchmark Test

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

Vercel vs. Harper Benchmark Test

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

Vercel vs. Harper Benchmark Test

Harper runs live, personalized apps 4–14x faster than Vercel by unifying data, logic, cache, and messaging in one runtime.

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.

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.

Stephen Goldberg

CEO & Co-Founder

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

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

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

Get Started

No Credit Card Required.

White arrow pointing right

White arrow pointing right

White arrow pointing right

White arrow pointing right