Data Enthusiast Testimonial

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Most real-time apps need a broker, a bridge, and a cache to keep state in sync. This is a live MQTT scoring demo on Harper, where the topic and the database record are the same write.

The Topic Is the Record: Real-Time Fan-Out Without a Broker, a Bridge, and a Cache

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

System Design

Blog

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

Austin Akers

Head of Developer Relations

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

Cross-region latency comes from distance, not slow queries. Why centralized data paths cost you latency, uptime, and money, with a benchmark you can run.

The Distance Problem: Why Centralized Data Paths Cost You Latency, Uptime, and Money

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Media Coverage

Harper Argues Against the Multi-System Stack and Releases 5.2

Media Coverage

InfoQ examines benchmark results comparing co-located and serverless architectures, highlighting faster personalized-data paths, serverless advantages under heavy fan-out, and the performance implications of eliminating network hops between services at scale.

Renato Losio

InfoQ Staff Editor

Media Coverage

Blog

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Kris Zyp

SVP of Engineering

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Kris Zyp

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Kris Zyp

Harper 5.2 attacks database performance on three fronts: a per-worker record cache validated through lock-free atomic version slots, isolated commit scheduling to keep database writes off the application thread, and query planner improvements that route through the shortest available data path.

Faster by Doing Less: How Harper 5.2 Engineers Database Performance

Kris Zyp

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Harper Recognized as an Honorable Mention in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

Announcement

News

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Aleks Haugom

Senior Manager of GTM

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Harper Recognized as an Honorable Mention in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

Aleks Haugom

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Harper Recognized as an Honorable Mention in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

Aleks Haugom

Harper’s inclusion highlights a broader shift toward integrated cloud-native platforms that unify data, caching, messaging, and application logic. The article explains how Harper’s distributed runtime and managed infrastructure reduce operational complexity, improve performance, and support modern applications and AI agents that require fast, reliable access to state, events, and tools.

Harper Recognized as an Honorable Mention in the 2026 Gartner® Magic Quadrant™ for Cloud-Native Application Platforms

Aleks Haugom

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

Cache

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

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.

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