Open Source Smartsheet Alternatives

NocoDB puts a spreadsheet in front of a database so people who will never write SQL can work with the data directly. Tables, columns and rows are created and edited in the browser, backed by SQLite or PostgreSQL.

Installation is a single Docker command for a local instance. For production there is an auto-upstall script that installs Docker, brings up NocoDB with PostgreSQL, Redis and a Traefik gateway, sets up and renews SSL for a domain you supply, and upgrades the deployment whenever you run it again.

The interface covers what a team actually does with shared data.

• Multiple view types: grid, gallery, form, kanban and calendar over the same underlying table.
• Field operations: sort, filter, group and hide columns without touching the schema.
• Varied cell types: links, lookups, rollups, formulas, attachments, currency and user fields.
• Sharing controls: bases and views publish publicly or stay protected behind a password.
• Role-based access: fine-grained permissions apply at several levels, including locked views.

An app store adds workflow integrations across chat, email and storage, covering Slack, Discord, Mattermost, SES, SMTP, S3, Google Cloud Storage and Minio among others. REST APIs and an SDK handle programmatic access with signed tokens, and binaries exist for macOS, Linux and Windows for quick local testing.

Teable is a database collaboration platform on PostgreSQL that presents tables through a spreadsheet-style interface, so data stays in a real database while the people using it never have to write SQL.

Self-hosting deploys four platforms at once. The database platform sits alongside an AI workflow engine, an agent sandbox that gives every AI session its own isolated container started on demand, and a deployment platform where each app your team publishes runs as its own long-lived container.

Both halves of the product, the classic base and the AI layer, cover a lot of ground.

• Views: grid, form, kanban, gallery and calendar views over the same tables.
• Spreadsheet mechanics: formulas, field conversion, filtering, grouping, sorting and aggregation.
• Collaboration: comments, record history, undo and redo, and real-time editing.
• AI chat: ask questions of your data and operate on it in natural language.
• App Builder: describe an app, an agent builds it in a sandbox and deploys it to its own address.
• Automations: record changes, schedules and webhooks trigger workflows that include AI steps.

Three deployment paths exist. Standalone self-hosting gives tables, collaboration, API and automation; the full-featured self-host adds the AI features and App Builder; and a hosted cloud runs everything for you. An existing standalone installation can gain the runtime plane while its data stays in place.

APITable looks like a spreadsheet and behaves like a database, with an API in front of both. Tables link to one another without limit, records and metadata are equally reachable over REST, and one workspace takes the place of the pile of trackers a growing team tends to accumulate.

The grid is drawn by a canvas rendering engine and stays responsive past a hundred thousand rows, while an operational transformation algorithm merges simultaneous edits from several people. The stack is TypeScript with Next.js and NestJS alongside Java with Spring Boot, released under the AGPL.

The workspace arrives with the pieces most teams otherwise bolt on separately.

• Seven view types: grid, gallery, mindmap, kanban, Gantt, calendar and form views over the same underlying data.
• Full-stack API: an API panel opens from the corner of any table, and access covers data and metadata alike.
• Widgets and automation: more than twenty open source widgets, customizable charts, formulas and robot actions.
• Permissions: folder, file and column permissions, with mirrors turning a view into row-level access.
• Enterprise controls: SAML, single sign-on, audit, automatic database backup, data export and watermarking.

Self-hosting runs through a docker compose install script, and four CPUs with eight gigabytes of memory are the recommended minimum. Container images are amd64 only, so Apple silicon hosts should expect poor performance for now. A hosted version and an online demo are both available for evaluation.

Grist is a hybrid of a spreadsheet and a database. Columns are named and hold one kind of data, as in a database table, yet they can still be filled by formula and recalculate when a referenced cell changes. That combination rescues the spreadsheet that quietly became a system of record.

Formulas are written in Python, with the full syntax and standard library alongside many familiar Excel functions. A formula timer diagnoses the slow ones, and an AI formula assistant drafts them using OpenAI, Llama or any OpenAI-compatible endpoint.

This repository, the Community edition, carries most of what the product does.

• SQLite storage: a document is a self-contained SQLite file, readable by any tool that reads SQLite.
• Access rules: control access to individual rows, columns and tables, based on cell values and user attributes.
• Dashboards: charts, card views, calendars and summary tables, laid out as linked widgets instead of one crowded table.
• Native forms: forms feeding the spreadsheet directly, with attachments, hidden fields and pre-population.
• Collaboration: threaded cell comments with mentions, live presence, and suggested changes for review.

Integrations include a REST API with an interactive console, configurable outgoing webhooks, import and export with Google Drive, Excel and CSV, and SCIM provisioning. Incremental imports let you add a month of new bank activity without duplicating what is already there.

grist-core is Apache 2.0 and self-hostable, with a desktop app and an in-browser build in separate repositories. Features exclusive to the hosted edition are listed explicitly rather than left to discover.

Baserow is a spreadsheet and database hybrid that grows into applications. A team starts by structuring data in a familiar grid, then adds the internal tools, workflows and dashboards that would otherwise be a separate build, and none of it requires code.

The stack is Django, Vue.js and PostgreSQL. The platform is headless and API first, with published documentation and an OpenAPI schema, and a built-in AI assistant named Kuma creates databases and workflows from natural language.

Several building blocks sit on top of the underlying tables.

• Applications: create portals and apps, then publish them on your own domain.
• Automations: run repetitive workflows without manual steps.
• Dashboards: visualize what the tables hold.
• Multiple views: work with records as grids, kanban boards or forms.
• Compliance: the project reports GDPR, HIPAA and SOC 2 Type II compliance.

One Docker command with a mounted data volume runs the whole thing, and guides cover Helm, Docker Compose, Heroku, Render, DigitalOcean, AWS, Cloudron, Railway and Elestio, with no storage restrictions when self-hosted. Everything outside the premium and enterprise tiers carries the MIT license, allowing commercial and private use. Note that the project moved from GitLab to GitHub, and while issues came across, merged and closed merge requests did not.