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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<meta
name="description"
content="PixelsDB is a cloud-native analytics project centered on Pixels, a high-performance columnar storage and compute engine for data lakes and warehouses."
>
<title>PixelsDB</title>
<link rel="preconnect" href="https://img.shields.io">
<link rel="stylesheet" href="styles.css">
</head>
<body>
<header class="site-header">
<div class="container site-header-top">
<a class="brand" href="index.html">
<span class="brand-mark" aria-hidden="true"></span>
<span class="brand-text">PixelsDB</span>
</a>
<a class="source-link" href="https://github.com/pixelsdb/pixels">pixelsdb/pixels</a>
</div>
<nav class="site-nav" aria-label="Primary">
<div class="container site-nav-list">
<a class="nav-link nav-link-active" href="index.html">Home</a>
<a class="nav-link" href="documents.html">Documents</a>
<a class="nav-link" href="publications.html">Publications</a>
<a class="nav-link" href="#research">Research</a>
</div>
</nav>
</header>
<main id="top">
<section class="hero hero-home">
<div class="container">
<div class="hero-copy">
<p class="eyebrow">Open analytics platform for data lakes and warehouses</p>
<h1>PixelsDB</h1>
<p class="hero-kicker">High-performance storage, serverless elasticity, freshness, and interactivity.</p>
<hr class="intro-divider">
<p class="hero-text">
The PixelsDB project is centered on <strong>Pixels</strong>, a columnar storage and compute
engine for analytical workloads. It is designed for on-premises and cloud-native storage,
integrates with mainstream query engines, and extends into serverless query processing,
web-based exploration, and CDC-driven data freshness.
</p>
<div class="hero-actions">
<a class="button button-primary" href="documents.html">Read the docs</a>
<a class="button" href="https://github.com/pixelsdb/pixels">Main repository</a>
<a class="button" href="publications.html">Publications</a>
</div>
</div>
</div>
</section>
<section id="overview" class="section">
<div class="container">
<div class="section-heading">
<p class="eyebrow">Overview</p>
<h2>Main features of PixelsDB</h2>
<p>
PixelsDB combines the core Pixels engine with elasticity, transactional freshness, and
interactive query experiences for modern analytical systems.
</p>
</div>
<div class="card-grid four-up">
<article class="card">
<h3>High-performance column store</h3>
<p>
Pixels is optimized for multiple storage systems including S3, HDFS, POSIX file
systems, NVMe SSDs, and other cloud-native or on-premises environments.
</p>
<a href="https://github.com/pixelsdb/pixels">Explore the main repo</a>
</article>
<article class="card">
<h3>Turbo</h3>
<p>
Turbo provides serverless elastic query processing, combining autoscaling execution
with serverless acceleration for bursty analytical workloads.
</p>
<a href="https://github.com/pixelsdb/pixels/tree/master/pixels-turbo">Read the Turbo module</a>
</article>
<article class="card">
<h3>Retina</h3>
<p>
Retina provides freshness and ACID transactions, enabling real-time synchronization
and consistent analytical access on evolving data.
</p>
<a href="https://github.com/pixelsdb/pixels">See Retina in Pixels</a>
</article>
<article class="card">
<h3>Rover</h3>
<p>
Rover provides flexible SLAs and interactivity through a web-based experience for
query execution, exploration, and natural-language-assisted workflows.
</p>
<a href="https://github.com/pixelsdb/pixels-rover">Open Pixels-Rover</a>
</article>
</div>
</div>
</section>
<section class="section section-alt">
<div class="container">
<div class="section-heading">
<p class="eyebrow">Why PixelsDB</p>
<h2>Built for modern analytical systems</h2>
</div>
<div class="card-grid four-up">
<article class="card">
<h3>Lakehouse-friendly storage</h3>
<p>
Pixels is designed for analytical tables in data lakes and warehouses, with a focus on
practical deployment across cloud-native and on-premises environments.
</p>
</article>
<article class="card">
<h3>Performance-oriented format</h3>
<p>
The project emphasizes high-throughput analytical access and reports up to two orders
of magnitude improvement over Parquet in targeted scenarios.
</p>
</article>
<article class="card">
<h3>Open ecosystem integrations</h3>
<p>
Connectors and related projects link PixelsDB to engines and tooling already common in
modern data platforms.
</p>
</article>
<article class="card">
<h3>Research-backed roadmap</h3>
<p>
The system evolves alongside published work on storage layout, serverless analytics,
and freshness for lake-style data systems.
</p>
</article>
</div>
</div>
</section>
<section id="research" class="section">
<div class="container">
<div class="section-heading">
<p class="eyebrow">Research</p>
<h2>Publications behind the project</h2>
<p>
PixelsDB draws from a series of research efforts in data lakes, wide-table layout
optimization, and serverless analytics.
</p>
</div>
<article class="publication">
<h3>Browse the full PixelsDB publication list</h3>
<p>See all papers, demos, abstracts, and recent work on the dedicated publications page.</p>
<p><a class="button button-primary" href="publications.html">View publications</a></p>
</article>
</div>
</section>
</main>
<footer class="site-footer">
<div class="container footer-layout">
<p>PixelsDB is an open GitHub-centered project for analytics systems research and engineering.</p>
<p><a href="https://github.com/pixelsdb">github.com/pixelsdb</a></p>
</div>
</footer>
</body>
</html>