# zero copy

Published articles for zero copy.

This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles.

## Strengthening Camera Support in Zephyr for Advanced Vision Applications

DevFeed: [Strengthening Camera Support in Zephyr for Advanced Vision Applications](<https://devfeed.tech/articles/strengthening-camera-support-in-zephyr-for-advanced-vision-applications-13980.md>)

Original publisher: [Read original article](<https://www.zephyrproject.org/strengthening-camera-support-in-zephyr-for-advanced-vision-applications/>)

Author: Zephyr Project

Published: 2026-09-04T21:12:17Z

Content type: article

Language: en

Sources: [Zephyr Project](<https://devfeed.tech/sources/zephyr-project.md>)

Topics: [Embedded Systems](<https://devfeed.tech/topics/embedded-systems.md>), [Embedded Software Dev](<https://devfeed.tech/topics/embedded-software-dev.md>), [Open Source](<https://devfeed.tech/topics/open-source.md>), [Framework](<https://devfeed.tech/topics/framework.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [object-detection](<https://devfeed.tech/topics/object-detection.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [Streaming](<https://devfeed.tech/topics/streaming.md>), [Robotics](<https://devfeed.tech/topics/robotics.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [blog](<https://devfeed.tech/tags/blog.md>), [cameras](<https://devfeed.tech/tags/cameras.md>), [development](<https://devfeed.tech/tags/development.md>), [embedded](<https://devfeed.tech/tags/embedded.md>), [embedded-systems](<https://devfeed.tech/tags/embedded-systems.md>), [events](<https://devfeed.tech/tags/events.md>), [india](<https://devfeed.tech/tags/india.md>), [industry-conference](<https://devfeed.tech/tags/industry-conference.md>), [object-detection](<https://devfeed.tech/tags/object-detection.md>), [open-source](<https://devfeed.tech/tags/open-source.md>), [open-source-summit](<https://devfeed.tech/tags/open-source-summit.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [robotics](<https://devfeed.tech/tags/robotics.md>), [streaming](<https://devfeed.tech/tags/streaming.md>), [vision](<https://devfeed.tech/tags/vision.md>), [zephyr](<https://devfeed.tech/tags/zephyr.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

This event recap examines proposed changes to Zephyr's camera and driver architecture for AI-driven vision workloads. The proposals include attaching metadata and inference results to individual video buffers and adding per-buffer callbacks to improve buffer ownership, reduce CPU wakeups, and support more manageable camera pipelines. The changes remain under exploration through prototypes and community discussions.

### Source excerpt

The Zephyr community came together at Open Source Summit India 2026 in Mumbai to share knowledge and explore developments, tooling, and real-world applications across embedded systems. In this second post event blog, we recap two lightning talks from the Zephyr track focused on camera support.

## RocksDB Performance and Zero-Copy

DevFeed: [RocksDB Performance and Zero-Copy](<https://devfeed.tech/articles/rocksdb-performance-and-zero-copy-41530.md>)

Original publisher: [Read original article](<https://dfa1.github.io/articles/rocksdb-performance-and-zero-copy.html>)

Author: Davide Angelocola

Published: 2026-08-08T00:00:00Z

Content type: article

Language: en

Sources: [Davide Angelocola](<https://devfeed.tech/sources/davide-angelocola.md>)

Topics: [rocksdb](<https://devfeed.tech/topics/rocksdb.md>), [C++](<https://devfeed.tech/topics/c-plus-plus.md>), [Java](<https://devfeed.tech/topics/java.md>), [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Cache](<https://devfeed.tech/topics/cache.md>)

Tags: [benchmark](<https://devfeed.tech/tags/benchmark.md>), [c-plus-plus](<https://devfeed.tech/tags/c-plus-plus.md>), [java](<https://devfeed.tech/tags/java.md>), [library](<https://devfeed.tech/tags/library.md>), [memory](<https://devfeed.tech/tags/memory.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rocksdb](<https://devfeed.tech/tags/rocksdb.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

This article examines zero-copy reads for an FFM-based RocksDB binding between C++ and Java. It describes callback-scoped memory management, pinned data, resource lifetimes, and benchmark results showing that zero-copy is not always faster for small values.

### Source excerpt

rocksdbffm, the FFM-based RocksDB binding I wrote about last time. Here's what it took to get reads down to zero allocations -- and what the benchmarks had to say about it.

## Нейро сети для самых маленьких. Часть первая (которая после нулевой). Удобство в прокрустовом ложе оптимизации

DevFeed: [Нейро сети для самых маленьких. Часть первая (которая после нулевой). Удобство в прокрустовом ложе оптимизации](<https://devfeed.tech/articles/article-24859.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/yandex/articles/1047072/>)

Author: eucariot (Яндекс, Yandex Cloud & Yandex Infrastructure)

Published: 2026-07-01T07:00:06Z

Content type: article

Language: ru

Sources: [Яндекс - Как мы делаем Яндекс / Статьи](<https://devfeed.tech/sources/source.md>)

Topics: [High-Performance Computing](<https://devfeed.tech/topics/high-performance-computing.md>), [GPU](<https://devfeed.tech/topics/gpu.md>), [InfiniBand](<https://devfeed.tech/topics/infiniband.md>), [NVLink](<https://devfeed.tech/topics/nvlink.md>), [Linux](<https://devfeed.tech/topics/linux.md>)

Tags: [ethernet](<https://devfeed.tech/tags/ethernet.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [gpudirect-rdma](<https://devfeed.tech/tags/gpudirect-rdma.md>), [high-performance-computing](<https://devfeed.tech/tags/high-performance-computing.md>), [infiniband](<https://devfeed.tech/tags/infiniband.md>), [linux](<https://devfeed.tech/tags/linux.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvlink](<https://devfeed.tech/tags/nvlink.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rdma](<https://devfeed.tech/tags/rdma.md>), [roce](<https://devfeed.tech/tags/roce.md>), [tcp](<https://devfeed.tech/tags/tcp.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

This introductory article in a series explains the infrastructure used to train and run neural networks and for high-performance computing. It surveys specialized technologies including GPUs and TPUs, RDMA, kernel bypass, NVLink, InfiniBand, and RoCE, arguing that specialized solutions can outperform and cost less than a generic Linux and Ethernet/IP stack at scale.

### Source excerpt

Это первая (после нулевой) статья из серии Нейро сети для самых маленьких, в которой мы разбираем инфраструктуру для запуска нейронных сетей. Для обучения и инференса нейросетей и для любых видов High Performance Computing используются специализированные технологии: GPU/TPU, RDMA, Kernel bypass, NVLink, InfiniBand, RoCE и другие. Про некоторые из них большинство только что-то слышали, но сталкиваться с ними не приходилось. Нельзя просто взять ванильный стек Linux, воткнуть в него 400Gb Ethernet+IP и получить рабочее решение. Почему? Потому что общее решение на масштабе в большинстве случаев проигрывает специализированным как в скорости, так и в стоимости. Как бы странно последнее ни звучало. Читать далее

## Introducing Apache Arrow Support in mssql-python

DevFeed: [Introducing Apache Arrow Support in mssql-python](<https://devfeed.tech/articles/introducing-apache-arrow-support-in-mssql-python-20347.md>)

Original publisher: [Read original article](<https://devblogs.microsoft.com/python/introducing-apache-arrow-support-in-mssql-python/>)

Author: Saumya Garg

Published: 2026-05-04T04:33:00Z

Content type: release

Language: en

Sources: [Microsoft Python Engineering](<https://devfeed.tech/sources/microsoft-python-engineering.md>)

Topics: [sql-server](<https://devfeed.tech/topics/sql-server.md>), [data-processing](<https://devfeed.tech/topics/data-processing.md>), [interoperability](<https://devfeed.tech/topics/interoperability.md>), [data](<https://devfeed.tech/topics/data.md>), [pandas](<https://devfeed.tech/topics/pandas.md>)

Tags: [apache-arrow](<https://devfeed.tech/tags/apache-arrow.md>), [arrow](<https://devfeed.tech/tags/arrow.md>), [azure](<https://devfeed.tech/tags/azure.md>), [azure-sql](<https://devfeed.tech/tags/azure-sql.md>), [client-driver](<https://devfeed.tech/tags/client-driver.md>), [data-processing](<https://devfeed.tech/tags/data-processing.md>), [interoperability](<https://devfeed.tech/tags/interoperability.md>), [pandas](<https://devfeed.tech/tags/pandas.md>), [python](<https://devfeed.tech/tags/python.md>), [python-driver-for-azure-sql](<https://devfeed.tech/tags/python-driver-for-azure-sql.md>), [python-driver-for-sql-server](<https://devfeed.tech/tags/python-driver-for-sql-server.md>), [sql-server](<https://devfeed.tech/tags/sql-server.md>), [sql-server-2025](<https://devfeed.tech/tags/sql-server-2025.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

Microsoft introduces Apache Arrow support in mssql-python, enabling SQL Server data to be fetched directly into Arrow structures for Polars, Pandas, DuckDB, and other Arrow-native libraries. The approach is intended to reduce Python object creation and memory overhead during data processing.

### Source excerpt

Reviewed by Sumit Sarabhai Fetching a million rows from SQL Server into a Polars DataFrame used to mean a million Python objects, a million GC allocations, and then throwing it all away to build a DataFrame. Not anymore. mssql-python now supports fetching SQL Server data directly as Apache Arrow structures - a faster and more [...] The post Introducing Apache Arrow Support in mssql-python appeared first on Microsoft for Python Developers Blog.

## How Tinybird's storage architecture works: S3, local caching, and zero-copy replication

DevFeed: [How Tinybird's storage architecture works: S3, local caching, and zero-copy replication](<https://devfeed.tech/articles/how-tinybird-s-storage-architecture-works-s3-local-caching-and-zero-copy-replication-18688.md>)

Original publisher: [Read original article](<https://www.tinybird.co/blog/tinybird-architecture>)

Author: Daniel Pozo, Irene Martínez

Published: 2026-03-02T10:00:00Z

Content type: article

Language: en

Sources: [Tinybird](<https://devfeed.tech/sources/tinybird.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [Caching](<https://devfeed.tech/topics/caching.md>), [Replication](<https://devfeed.tech/topics/replication.md>), [cloud-infrastructure](<https://devfeed.tech/topics/cloud-infrastructure.md>)

Tags: [architecture](<https://devfeed.tech/tags/architecture.md>), [caching](<https://devfeed.tech/tags/caching.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [engineering-excellence](<https://devfeed.tech/tags/engineering-excellence.md>), [object-storage](<https://devfeed.tech/tags/object-storage.md>), [replication](<https://devfeed.tech/tags/replication.md>), [run](<https://devfeed.tech/tags/run.md>), [s3](<https://devfeed.tech/tags/s3.md>), [ssd](<https://devfeed.tech/tags/ssd.md>), [storage](<https://devfeed.tech/tags/storage.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

This article explains how Tinybird runs ClickHouse on object storage using local SSD caching, zero-copy replication, and a packed part format. It states that the format reduces S3 costs by 30-40%.

### Source excerpt

How we run ClickHouse on top of object storage with local SSD caching, zero-copy replication, and a packed part format that cuts S3 costs by 30-40%.

## How Tinybird Built Branches to Share Production Data Without Copying It

DevFeed: [How Tinybird Built Branches to Share Production Data Without Copying It](<https://devfeed.tech/articles/how-we-built-branches-sharing-production-data-without-copying-it-18398.md>)

Original publisher: [Read original article](<https://www.tinybird.co/blog/branches-deep-dive>)

Author: Alberto Romeu

Published: 2026-02-26T00:00:00Z

Content type: article

Language: en

Sources: [Tinybird](<https://devfeed.tech/sources/tinybird.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [Kafka](<https://devfeed.tech/topics/kafka.md>), [Amazon S3](<https://devfeed.tech/topics/amazon-s3.md>), [CI/CD](<https://devfeed.tech/topics/cicd.md>)

Tags: [ci-cd](<https://devfeed.tech/tags/ci-cd.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [engineering-excellence](<https://devfeed.tech/tags/engineering-excellence.md>), [kafka](<https://devfeed.tech/tags/kafka.md>), [s3](<https://devfeed.tech/tags/s3.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

An engineering article about Tinybird branches, covering zero-copy production-data sharing through ClickHouse metadata, Kafka consumer group isolation, S3 sample imports, and CI/CD preview deployments.

### Source excerpt

The engineering behind Tinybird branches: zero-copy partition sharing via ClickHouse metadata, Kafka consumer group isolation, S3 sample imports, and CI/CD preview deployments.

## ESP\_IMAGE\_EFFECTS v1.0.0 Release: Image Processing for Embedded Devices

DevFeed: [ESP\_IMAGE\_EFFECTS v1.0.0 Release: Image Processing for Embedded Devices](<https://devfeed.tech/articles/esp-image-effects-release-lightweight-powerful-and-made-for-a-colorful-world-13717.md>)

Original publisher: [Read original article](<https://developer.espressif.com/blog/2025/08/announcing_esp_image_effects/>)

Author: John Lee

Published: 2025-08-29T00:00:00Z

Content type: release

Language: en

Sources: [Blog on Developer Portal](<https://devfeed.tech/sources/blog-on-developer-portal.md>)

Topics: [Image processing](<https://devfeed.tech/topics/image-processing.md>), [Library](<https://devfeed.tech/topics/library.md>), [Embedded Software Dev](<https://devfeed.tech/topics/embedded-software-dev.md>), [Microcontroller](<https://devfeed.tech/topics/microcontroller.md>)

Tags: [blog](<https://devfeed.tech/tags/blog.md>), [embedded-systems](<https://devfeed.tech/tags/embedded-systems.md>), [image-color-space](<https://devfeed.tech/tags/image-color-space.md>), [image-crop](<https://devfeed.tech/tags/image-crop.md>), [image-effects](<https://devfeed.tech/tags/image-effects.md>), [image-processing](<https://devfeed.tech/tags/image-processing.md>), [image-rotate](<https://devfeed.tech/tags/image-rotate.md>), [image-scale](<https://devfeed.tech/tags/image-scale.md>), [library](<https://devfeed.tech/tags/library.md>), [multimedia](<https://devfeed.tech/tags/multimedia.md>), [release](<https://devfeed.tech/tags/release.md>), [rotation](<https://devfeed.tech/tags/rotation.md>), [zero-copy](<https://devfeed.tech/tags/zero-copy.md>)

### AI overview

Espressif announces ESP_IMAGE_EFFECTS v1.0.0, an image processing library for embedded devices. The article describes its unified APIs, SIMD optimization, zero-copy memory design, and support for rotation, color space conversion, and image scaling.

### Source excerpt

Espressif's ESP_IMAGE_EFFECTS component is a powerful image processing library that can do common image processing operations such as scaling, rotation, cropping, and color space conversion. This article introduces the library, shows how to use it in processing images, and provides usage examples.