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Discover how Harper successfully transitioned to a sustainable commercial open source platform. Ethan Arrowood details their split core licensing strategy, engineering velocity, and practical framework for building true community trust.

Event

Discover how Harper successfully transitioned to a sustainable commercial open source platform. Ethan Arrowood details their split core licensing strategy, engineering velocity, and practical framework for building true community trust.

Ethan Arrowood

Head of Open Source

Event

Building Sustainable Open Source: The Harper Story

Ethan Arrowood

Discover how Harper successfully transitioned to a sustainable commercial open source platform. Ethan Arrowood details their split core licensing strategy, engineering velocity, and practical framework for building true community trust.

Event

Building Sustainable Open Source: The Harper Story

Ethan Arrowood

Event

Building Sustainable Open Source: The Harper Story

Discover how Harper successfully transitioned to a sustainable commercial open source platform. Ethan Arrowood details their split core licensing strategy, engineering velocity, and practical framework for building true community trust.

Ethan Arrowood

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

Cache

Comparison

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.

Aleks Haugom

Senior Manager of GTM

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

End-to-end latency in real-time pipelines comes from coordination across systems, not from any single component. Four common workloads, tested two ways, show where multi-hop architectures compound delays and where collapsing storage, messaging, and compute into one runtime changes the math.

Kafka-Centered Stacks vs. a Single Harper Cluster: Where Real-Time Latency Actually Comes From

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.

Your API cache is secretly a database

Cache

Tutorial

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.

Kris Zyp

SVP of Engineering

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.

Your API cache is secretly a database

Kris Zyp

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.

Your API cache is secretly a database

Kris Zyp

Most teams treat a cache as a black box: URL-keyed blobs with a TTL, useful for speed and nothing else. In Harper, cached data lands in a real table inside the same query engine. That means filtering, joining, real-time subscriptions, and vector search all work against it.

Your API cache is secretly a database

Kris Zyp

Learn how to keep AI-assisted side projects on track using a repo-native coordination layer that preserves context across session gaps.

How to Keep Massive AI-Assisted Side Projects on Track

A.I.

Blog

Learn how to keep AI-assisted side projects on track using a repo-native coordination layer that preserves context across session gaps.

Aleks Haugom

Senior Manager of GTM

Learn how to keep AI-assisted side projects on track using a repo-native coordination layer that preserves context across session gaps.

How to Keep Massive AI-Assisted Side Projects on Track

Learn how to keep AI-assisted side projects on track using a repo-native coordination layer that preserves context across session gaps.

How to Keep Massive AI-Assisted Side Projects on Track

Learn how to keep AI-assisted side projects on track using a repo-native coordination layer that preserves context across session gaps.

How to Keep Massive AI-Assisted Side Projects on Track

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.

Introducing Structon: Random-Access Binary Encoding for JavaScript

JavaScript

Tutorial

Deserializing entire records to read one field is a bottleneck at scale. Structon stores objects in a binary format where any field is reachable by byte offset, with lazy getters that never allocate until you access a property. It's the encoding Harper has used internally for years, now a standalone package.

Kris Zyp

SVP of Engineering