796adaeca6
`file_change` is the biggest relation of the database: 683 GB in production, of which almost all the TOAST is dead space (the legacy data is already migrated to `file_data`; what is left is the xlog of the revisions, 4.4 kB on average). It grows with every save of a file and every version, and its rows are spread over the whole table, so every query that filters by a file has to walk all of it. The table is now partitioned by `HASH (file_id)` with 16 partitions, the same bounds as `file_data`, so the queries that filter by a file can prune to one partition and the join between the two tables is resolved partition by partition. The primary key has to include the partition key, so it becomes `(file_id, id)`, and every access path of the table filters by `file_id` accordingly: the snapshot commands require it (2.19), the frontend sends it, and the garbage collector locks the pending rows by their `(file_id, id)` pair. The migration creates the partitioned table with the final schema and copies the rows, keeping the old one aside as `file_change_legacy` for the rollback. The copy happens inside the transaction of the migration, so it does not fit a big instance: there the migration is marked as applied and the procedure of `operations/` does it by hand, in phases, driven by the `updated_at` watermark. Along the way: - every mutation of the table moves `updated_at` to the moment of the mutation, so the phased copy does not lose the rows changed while it runs. It is never set to the `deleted_at` of the row, which for the system snapshots is a date in the future. - a new `kind` column tells the snapshots (1) and the revisions (2) of the table apart, and the two paths that insert in it fill it. It has no default on purpose, so an insert that forgets it fails instead of storing the wrong kind silently. It is a reserve: the queries still tell a snapshot from a revision by its label, and no constraint ties the two together. - the revision does not repeat the features of the file anymore: they were 348 bytes written on every save and nobody read them from there. - the legacy file data backend is gone, and with it the `data`, `data_ref_id` and `data_backend` columns, which nobody wrote anymore. - the migration copies the legacy blobs of the snapshots to `file_data` before the column goes away, and stops when a snapshot with legacy data is left without its blob: the backend is better down than losing content. - the foreign key of the legacy table on `file_id` goes away with the copy: it is `NO ACTION`, so while the legacy table has rows, the objects GC cannot delete the files they point to. - the quota of the snapshots of a team resolves the files of the team first and counts their versions with `= ANY`, instead of joining the team with every version of the table. - the pool sets `enable_partitionwise_join` on every connection, so the join between the two partitioned tables is resolved partition by partition. - the snapshot lookup reports an unknown snapshot with its own error instead of the generic "object not found" of the database helper, and the decode script fails instead of printing an empty JSON. - the procedure of `operations/` stops the backend and the workers during the cutover: the pool keeps server-side prepared statements, and a prepared statement holds the OID of the table it was prepared with, so a connection would keep writing to the legacy table after the rename. - the procedure creates the partitions with their final name, so the result is the schema a new installation gets, and its verification checks the names and not only how many there are. - the index of the system snapshots is gone: it filtered them by `deleted_at IS NULL`, and they always carry a deletion date in the future, so it never matched a row. - the configuration guide, the memories and the docstring of the decode script say that the `legacy-db` backend is gone, instead of offering a value that takes the service down. - a test fixes the schema the migration leaves: the 16 partitions with their name, the primary key, the foreign keys, the check of the kind, the six indexes, the absence of the legacy columns, and that an insert without a kind or with an unknown one fails. Closes #12416 AI-assisted-by: glm-5.3-flash AI-assisted-by: minimax-m3.1-flash
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Penpot is the open-source design platform for teams that build digital products at scale.
Penpot’s key strength lies in giving you full ownership of your design infrastructure. Built on open source and designed for self-hosting, it puts teams in complete control of their design environment supporting strict compliance and governance requirements. Whether used in the browser or deployed on your own servers, Penpot works with open standards like SVG, CSS, HTML, and JSON.
Real-time collaboration strengthens this foundation, helping teams scale and bring design closer to the product through top-tier capabilities. Additionally, developers feel at home using Penpot, because design is expressed as code, enabling a direct translation and shipping products faster.
Best-in-class native Design Tokens provide a single source of truth between design and development. They ensure consistency, improve collaboration, and make it easier to manage complex design systems.
The MCP server takes it further by enabling multi-directional workflows between design and code. A powerful open API and plugin system makes the workspace programmable, enabling automation, AI-driven workflows, and integrations with the tools and systems you already use.
With CSS Grid and Flex Layout, teams can design responsive interfaces that behave like real code from the start.
Combined, these features turn Penpot into a full-stack design platform for building scalable design systems and fully integrated product development processes.
If your organization is scaling and needs extra support, we’re here to help. Talk to us
Table of contents
Why Penpot
Penpot connects design, code, and AI workflows through a code-based approach, making designs readable by developers and AI via the MCP server. This approach helps teams ship what’s actually designed and manage design systems at scale with powerful design tokens. As a self-hosted, open-source and real-time collaboration platform, Penpot offers full flexibility, security, and ownership without vendor lock-in. Learn more about why Penpot is the platform for your team.
Plugin system
Penpot plugins let you expand the platform's capabilities, give you the flexibility to integrate it with other apps, and design custom solutions.
Designed for developers
Penpot was built to serve both designers and developers and create a fluid design-code process. You have the choice to enjoy real-time collaboration or play "solo".
Inspect mode
Work with ready-to-use code and make your workflow easy and fast. The inspect tab gives instant access to SVG, CSS and HTML code.
Integrations
Penpot offers integration into the development toolchain, thanks to its support for webhooks and an API accessible through access tokens.
Building Design Systems: design tokens, components and variants
Penpot brings design systems to code-minded teams: a single source of truth with native Design Tokens, Components, and Variants for scalable, reusable, and consistent UI across projects and platforms.
Getting started
Penpot is the only design & prototype platform that is deployment agnostic. You can use it in our SAAS or deploy it anywhere.
Learn how to install it with Docker, Kubernetes, Elestio or other options on our website.
Penpot Enterprise
Penpot Enterprise is our paid plan for organizations that need to scale their design work across multiple teams with advanced governance, security, and administration. Manage teams and access from a centralized Admin Console, configure advanced permissions, and connect your identity provider through SSO. Available for cloud and self-hosted environments, it combines enterprise controls with Penpot’s open-source foundation and open standards.
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Penpot is a Kaleidos’ open source project