Members
The lab spans core maintainers, research students, and open-source collaborators who build PixelsDB and its surrounding ecosystem.
Meet the member groupsPixels Lab
People, systems research, and open-source collaboration
Pixels Lab brings together the members, research tracks, student work, publications, and partners behind PixelsDB across storage, serverless analytics, freshness, and interactive data systems.
Research projects
Pixels, Turbo, Retina, and Rover define the current portfolio for performance, elasticity, freshness, and interactivity.
Browse the project tracksPublic record
Publications, awards, sponsors, and student work provide the public view of how the lab advances systems ideas into working artifacts.
Explore the lab outputsMembers
Researchers, builders, and collaborators
Pixels Lab combines systems research with production-minded engineering across the core engine and its integrations.
Core maintainers
The main repository concentrates storage, execution, metadata, and connector work in a shared engineering codebase.
Open the core repositoryResearch students
Student contributors prototype new ideas in serverless query processing, data freshness, web interactivity, and benchmarking.
See student projectsOpen-source collaborators
Community members extend the ecosystem through documentation, issue reports, integrations, and downstream experimentation.
Visit the GitHub organizationResearch Projects
The current Pixels Lab portfolio
The lab roadmap is organized around four complementary systems tracks that share the same analytical data foundation.
Pixels
A high-performance column store built for multiple storage backends, including S3, HDFS, POSIX file systems, and NVMe SSDs.
Turbo
Serverless elastic query processing that scales analytical execution up and down with workload demand.
Retina
Freshness and ACID transactions for lakehouse-style analytics where data changes must remain visible and correct.
Rover
Flexible SLAs and interactive exploration that make the system more responsive to a wide range of user expectations.
Student Projects
Teaching systems and student-led exploration
Coursework repositories, teaching engines, and benchmark studies give students a path into open data systems research with PixelsDB.
Teaching engines
Educational systems such as mini-pixels distill the core design ideas behind Pixels into a format suited for learning and experimentation.
Browse student project detailsCoursework and labs
Course material and hands-on assignments connect analytical storage, query execution, and cloud systems topics to concrete artifacts.
Open the student projects pageBenchmark studies
Student work also covers elasticity benchmarks, user studies, and container-based systems evaluation.
View benchmark-oriented projectsPublications
Research papers and public artifacts
Publications document the ideas behind the lab's storage, serverless, freshness, and interactive systems work.
Systems papers
The research page collects the publication record for PixelsDB and the broader Pixels Lab agenda.
Open the publications pageDesign context
Publications connect the engine architecture to topics such as columnar storage, cloud elasticity, and fresh analytical tables.
Read the research overviewOpen-source traceability
Repository history and public documentation make it easier to follow how research ideas become working implementations.
Explore the DeepWikiAwards
Recognition and project milestones
The lab's progress is visible through publications, open-source releases, benchmarks, and reproducible systems artifacts.
Research recognition
Publication results and supporting artifacts provide the clearest public record of technical recognition for the lab's work.
See the publication recordEngineering milestones
Major capabilities surface as open-source milestones across the core repository and the wider PixelsDB organization.
Browse the organizationArtifact visibility
Benchmarks, documentation, and public code make the lab's progress inspectable and reproducible for collaborators.
Read the documentationSponsors
Partners and support channels
Pixels Lab is built to support collaboration with research groups, infrastructure providers, and open-source users evaluating modern analytics systems.
Infrastructure-aligned design
The system targets object stores, distributed file systems, POSIX environments, and local SSD-backed deployments, making partnership and evaluation straightforward.
Open collaboration
GitHub is the main coordination surface for contributors, adopters, and institutions interested in supporting the ecosystem.
Connect through GitHubResearch engagement
Sponsors and collaborators can track the direction of the lab through research outputs, technical documentation, and ongoing repository activity.
Follow the research agenda