TL;DR:
What is Grist? It’s an open‑source spreadsheet‑database: you work like in a spreadsheet, but with the structure of a relational database. Powerful formulas (up to Python), views and widgets for small dashboards, collaboration and very granular permissions.
Core vs Enterprise
- Core (open source): free, self‑hostable, almost all features. Perfect for SMEs/non‑profits/teams.
- Enterprise: same foundations, with SSO, audit, support, branding, dedicated hosting and increased limits. Useful for IT departments and large‑scale deployments.
Compared to proprietary tools
- Airtable: more polished and immediate, but expensive, cloud‑dependent and limited. Grist wins on sovereignty, control (self‑hosting) and power (Python, granular permissions).
- Power BI: heavy, multi‑source BI, very powerful but complex and licensed. Grist provides a light BI focused on “live” data (you edit and visualise in the same place).
- Google Data Studio (Looker Studio): excellent for free reporting, but not for managing or editing data. Grist combines data management with simple visualisation.
For everyday BI
- Ideal for properly centralising business data, calculating simple KPIs, prototyping reports and giving autonomy to non‑technical teams.
- Not made for big data/OLAP cubes → can be combined with a BI tool when needed.
Data sovereignty
- Self‑hosting, controlled data location, portable format (SQLite), auditable code, zero vendor lock‑in. Better compliance and independence.
When to choose Grist?
- If you want a single tool for entering, structuring and reading your data with small dashboards while retaining technical and financial control.
- Keep Power BI/Data Studio for advanced analyses and large‑scale report distribution.
Recommended first step
- Launch a pilot (1–2 concrete use cases), model the tables, create 2–3 views/graphs, test the permissions, then decide: Core (autonomy) or Enterprise (governance/SSO/support).
Introduction
Organising and analysing data is a common challenge in organisations. Between shared Excel sheets, specialised databases and new online tools, professionals have many choices – but often at the cost of compromises on flexibility, cost or control over data. Grist is a modern tool that aims to meet this challenge by positioning itself at the intersection of spreadsheets, databases and business applications. Built as open source, Grist offers the ease of a spreadsheet while bringing the robustness of a relational database. In this article, we will explore Grist Core (the free version) and Grist Enterprise, comparing Grist with popular proprietary solutions such as Airtable, Power BI or Google Data Studio. We will see how Grist can integrate into a Business Intelligence (BI) context for non‑technical professional needs, and why its open‑source model contributes to data sovereignty.
Grist sits at the crossroads of the spreadsheet, the database and application‑creation tools. This diagram illustrates how Grist combines these three worlds into a single tool.
What is Grist? An open‑source spreadsheet‑database
Grist presents itself as an enhanced spreadsheet running on a database engine. In other words, it looks like a familiar spreadsheet, but under the hood each sheet is a relational database. As a specialist article describes: “it looks like a spreadsheet but works like a relational database under the hood. Each column behaves like a field with a defined type, and each row acts like a structured record.” This hybrid architecture allows you to link tables together, avoid duplicating information and apply formulas to an entire column rather than a single cell. In short, Grist combines the flexibility of Excel with the rigour of Access in one tool.
Among Grist’s key features are:
- A familiar spreadsheet‑style interface, with a grid of cells for entering and viewing data.
- Relational power: ability to create relationships between tables (like in an SQL database) in order to structure connected data (e.g., linking a Clients table to an Orders table).
- Custom views: you can create multiple views of the same table (table, cards, forms, charts, kanban, etc.) to visualise the data from different angles without duplicating it. For example, a dashboard can display side by side the list of projects and a pie chart of status distribution, both driven by the same data.
- Visualisation and dashboards: Grist allows you to embed charts and interactive widgets directly into your pages. It is possible to design real dashboards by combining several widgets dynamically filtered by selections, somewhat like pivot tables or BI filters.
- Powerful formulas: in addition to classic spreadsheet functions, Grist natively supports the Python language in formulas. This opens the door to advanced calculations and sophisticated automations that are impossible to achieve in Excel or Airtable (e.g., automatic data cleaning, complex statistical calculations). However, note that Grist’s advanced features may require some knowledge of Python, which can be a learning curve for non‑technicians. The good news is that it is not necessary to know Python to start: you can use Grist like a normal spreadsheet, and only use Python scripts to go further.
- Real‑time collaboration: like Google Sheets or Airtable, Grist is designed for collaborative online work. Multiple users can edit simultaneously, with change tracking and version history to revert if needed.
- Granular access controls: a particularly welcome feature in a professional context, Grist allows you to define very fine‑grained permissions – down to the row or cell level. For example, you can give each salesperson access only to their own client records, or hide certain sensitive columns from specific users. This level of granular security is rarely available in equivalent consumer tools.
- Integrations and API: Grist integrates into an existing information system via a REST API and connectors. It can communicate with automation tools (such as n8n or Zapier) and import/export data via CSV or via its native format (based on SQLite). Data portability is an important asset: Grist’s file format is a standalone SQLite database, which means your data remains readable and usable outside the application.
- Flexible deployment: as open source, Grist offers a self‑hosting option. You can use the cloud version hosted by the Grist developers, or install Grist on your own server (via a simple Docker container, a desktop application or even entirely in the browser). This flexibility allows you to adapt Grist to your organisation’s IT policies, especially if you need to keep data in‑house.
In summary, Grist is a versatile tool that adapts to many use cases: project management, client follow‑up (CRM), inventory, activity reports, etc. It brings more structure and automation than a classic spreadsheet, without requiring the technical skills of a pure database solution.
Grist Core vs Grist Enterprise: two offerings for different needs.
The DNA of Grist is open source. Grist Core refers to the base of the software available freely under an Apache 2.0 licence. Anyone can install Grist Core, use it, modify it and distribute it at no cost. This is the community version, rich in features, which constitutes the heart of the product. Grist Core benefits from active development supported by the community and even by public bodies (as an anecdote, the project received contributions from the French National Agency for Territorial Cohesion, proof of the interest in a sovereign tool).
In parallel, the publisher offers hosted Grist services (cloud) with subscription tiers, and a Grist Enterprise offering for organisations with advanced requirements. This “hybrid” business model – a free core complemented by paid services – ensures funding for development while maintaining free access to the essential features. Concretely, what are the differences between Grist Core (free) and the paid offers?
- Volume limitations: in self‑hosted mode, Grist Core does not set an arbitrary size limit, aside from technical constraints (performance may decrease on very large volumes, beyond hundreds of thousands of rows). On the free cloud service, a document is limited to ~5,000 records per document, which suits small projects. The paid plans (Pro, Team) extend these limits (up to 150,000 rows per document for the Team offer). In Enterprise or self‑hosted environments, you can theoretically go beyond, but Grist remains optimised for small to medium data sets (typically < 150k rows per base).
- Support and services: the paid offers include priority technical support and professional services (consulting, implementation assistance). For a company deploying Grist at scale, this support can be valuable. The community version relies on community support (forums, Discord, online documentation).
- Enterprise features: some features target the needs of large organisations in terms of IT integration. For example, Grist Enterprise offers SSO (Single Sign‑On) integration with the corporate directory, custom domain and branding, audit logs (advanced tracking of access and changes), multi‑site management and centralised administration controls. These functions, unnecessary for individual use or SMEs, become important in a corporate context (security, compliance, management of many users).
- Dedicated hosting: an organisation under an Enterprise licence can opt for a dedicated server managed by Grist Labs or deploy the instance on its internal infrastructure with support from the publisher. This guarantees isolated performance and full control of the environment, meeting the strict policies of some IT departments. In free self‑hosting, you also have complete control since you manage the server yourself – the difference is that the support and service guarantee rest entirely on you.
In short, Grist Core is sufficient in most cases to get started and even for serious use within a small team or an SME. The free tool already offers almost all features (Python formulas, widgets, API, etc.). Moving to a paid plan is justified if you want the convenience of the cloud without technical management, a guaranteed support, or enterprise functions (SSO, audit, etc.). The existence of these two versions illustrates well the project’s goal: to democratise access to a powerful tool (via free open source), while offering large organisations a professional path supporting the product’s development.
Comparison: Grist versus proprietary solutions
Many tools allow you to manage data and dashboards without coding. Let’s see how Grist positions itself against some emblematic proprietary competitors such as Airtable, Microsoft Power BI and Google Data Studio (Looker Studio).
Grist vs Airtable
Airtable is often cited as the leader of “spreadsheet‑databases” for the general public. Its very polished online interface and numerous integrations have made it a popular choice for marketing, operations or product teams who want a tool that is quick to grasp. Airtable offers visual databases with forms, kanban views, simple automations… basically an all‑in‑one experience on Airtable’s cloud. However, several limitations of Airtable lead companies to look for alternatives: a cost that quickly rises with the volume of data, technical limitations (simplified formulas, no real SQL or Python), and growing concerns about data location (Airtable hosts everything on its servers, outside Europe for example).
Facing this, Grist bets on openness and control. Being open source, Grist can be entirely self‑hosted, eliminating any dependence on a third‑party provider and significantly reducing costs for large teams. Where Airtable imposes its own limits (e.g., number of records according to the plan, functions available only on higher plans), Grist offers complete autonomy: your data are stored with you, with no vendor lock‑in, and the software does not artificially restrict you. Functionally, Grist stands out with its Python formulas that allow complex calculations or automations far beyond Airtable’s proprietary formula language. For example, calculating an advanced indicator involving several tables or cleaning text data is much more feasible in Grist thanks to Python. Grist also offers granular access rules down to the cell, whereas Airtable is limited to sharing views or entire tables. In return, Airtable retains exemplary ergonomics and a very gentle learning curve for beginners. On this point, Grist may seem less “plug‑and‑play” visually – it does not yet have Airtable’s gallery of ready‑made templates nor its aesthetic polish. Users used to Excel or Google Sheets will quickly adapt to Grist, but a more novice audience might find Airtable more appealing initially. It is a choice between immediate simplicity and long‑term power/control.
In summary: if your priority is data sovereignty, technical flexibility and scalable use cases, Grist scores decisive points against Airtable. On the other hand, if you are looking for a hosted “turn‑key” tool with lots of templates to get started in a few minutes, Airtable remains a reference – while keeping in mind that you will have to pay to exceed its limits, and accept entrusting your data to an external cloud service.
Grist vs Microsoft Power BI
Microsoft Power BI is a full‑fledged Business Intelligence tool, widely used in companies to create interactive dashboards, reports and advanced data analyses. It is important to note that Power BI and Grist do not belong exactly to the same category of tools: Power BI is software purely oriented toward data analysis and visualisation, whereas Grist is primarily a data management platform (with an application and spreadsheet aspect). A member of the Grist community sums up the difference well: “Grist is closer to Excel – you insert and manage the information directly – while Power BI and its peers are used to transform, analyse and visualise data coming from elsewhere”. In short, in Grist your data reside in the tool (like in a spreadsheet, modifiable on the fly), whereas with Power BI you connect to external sources (database, files) and create dashboards, without editing the source data via Power BI. If when viewing a Power BI chart you notice a data error, you will need to correct the underlying source (Excel, SQL…) and then refresh – whereas in Grist, you could edit the value directly in the table and the chart would update instantly.
From a non‑technical professional’s point of view, what should be retained? Power BI is a very powerful tool for consolidating large volumes of data from different sources, applying complex analytical formulas (DAX in Power BI), and sharing highly interactive dashboards across the enterprise. However, this power has a downside: Power BI is a relatively complex ecosystem to master for a non‑technician. Data preparation, report design and model optimisation often require the intervention of experts (BI analysts, data scientists). Moreover, Power BI being a Microsoft product, collaborative use often requires paid licences (Power BI Pro per user, or a Premium licence) and the Microsoft 365 environment. In terms of sovereignty, Power BI reports are generally hosted on Microsoft’s Azure cloud (unless deploying a Report Server on‑premises, a heavy option), which can raise questions about data location and dependence on Microsoft.
Grist, for its part, does not claim to compete with all the analytical capabilities of Power BI: it is not a big‑data visualisation tool or a classic enterprise BI. However, for light and agile BI at the level of a team or an SME, Grist can play a very relevant role. It allows you to centralise varied data in structured tables, apply formulas or Python scripts to calculate indicators, and build simple dashboards integrated into the tool. A marketing manager, for example, could aggregate monthly sales data in Grist and create a report page with trend charts, without having to master a complete BI software. The learning curve will be much easier than Power BI for someone who knows how to use Excel, because the interface remains that of a spreadsheet, with the expected menus and behaviour (sorting, filters, copy‑paste, etc.). In addition, Grist’s integration with other tools (via API or exports) means it can be used in tandem with BI solutions: one can imagine entering cleaned data into Grist, then exporting them to a tool like Power BI if heavier analyses become necessary. Thus, Grist occupies an intermediate niche: more interactive and focused on raw data than Power BI, but also less sophisticated for multi‑source analysis or advanced graphic layout.
In summary, Grist and Power BI meet different needs. For a small structure or a department that wants a single tool where it can store its data and quickly extract views and reports without BI expertise, Grist is an excellent option (with the bonus of open source and self‑hosting to keep control of the information). For a company that already has a data infrastructure and dedicated analysts, Power BI will doubtless remain indispensable for strategic dashboards on large volumes – but Grist could then serve as a complementary solution, for example for specific internal applications or more operational tracking needs.
Grist vs Google Data Studio (Looker Studio)
Google Data Studio, renamed Looker Studio, is Google’s free tool for creating interactive online reports. Like Power BI, it is purely a visualisation solution: Data Studio does not store the data, it connects to sources (Google Sheets, BigQuery, files, etc.) and lets you compose dashboards with charts, tables and filters. Its main advantage is being free and relatively easy to use to quickly create attractive reports, particularly for marketing or web analytics (it naturally plugs into Google Analytics, Google Ads, etc.). In a context where a decision‑maker wants a one‑click, up‑to‑date summary report, Data Studio is relevant. However, this simplicity comes with limits: fewer types of visualisations and data transformations than professional BI solutions, and above all no ability to edit the data or perform complex calculations beyond a few basic calculated fields.
Compared to Grist, we find partly the same contrast as with Power BI: Data Studio is an excellent reporting tool but it is not designed for collaborative data management. It assumes that your data live elsewhere (in a data warehouse, a Google sheet, etc.) and will simply represent them. Grist, by contrast, offers a space where the data live: you can import them, modify them, organise them, then create inside Grist your displays (lists, charts…). A strength of Grist is that you can combine on the same page different views from linked tables: for example, display a list of projects and next to it a chart detailing the tasks of the selected project – this kind of interactive master/detail view is not directly doable in Data Studio. Moreover, in terms of data sovereignty, Data Studio being a Google service, your dashboards (and the data cached for display) transit through Google’s servers. For some organisations (public bodies, associations dealing with sensitive data, etc.), this may be a barrier in terms of compliance or confidentiality. With Grist, in self‑hosted mode, you are guaranteed that nothing leaves your server: even the charts and analyses stay internal.
In terms of use for a non‑technical audience, Data Studio is probably more immediate if the sole objective is to communicate figures in graph form. For example, a consultant could create a marketing report for a client on Data Studio in a few hours. By contrast, if the need evolves into “having a small internal application where the team enters data and gets dynamic reports”, Data Studio will not suffice. Grist may then prove more appropriate, because it combines data entry, storage and visualisation in a single platform. Thus you can design in Grist a mini CRM or indicator tracking where collaborators feed the tables over time and consult the results via filtered views, all without leaving the tool.
In summary, Data Studio/Looker Studio is an excellent tool for presenting data externally, whereas Grist is a tool for internal data management and analysis. If your aim is to build a marketing report to share with a client, Data Studio is suitable. If you want to give your team a way to manage its data daily and extract basic decision‑making views, Grist offers a more integrated solution under your full control.
Grist in a BI context: what role for “open‑source BI” in organisations?
Business Intelligence (BI) often evokes heavy data warehouse infrastructures, ETLs and specialised tools. But not all organisations have these extreme needs: for many SMEs, non‑profits or departments within large companies, the objective is first to properly centralise business data and obtain control indicators simply. It is precisely in this niche that Grist can operate. One can see Grist as a light BI tool coupled with an operational database. For example: a charity could use Grist to consolidate its list of members, donations received, events organised, then create a dashboard page with the total donations per quarter and the list of upcoming events. All of this would be accessible to authorised members, who could update the data live when necessary. No developer or complex infrastructure needed – a volunteer comfortable with Excel could set this up on Grist.
Another BI scenario for Grist is prototyping and flexibility. Imagine that a finance department wants to test a new reporting model. Before mobilising the BI department to create data pipelines, they can structure a model in Grist, import some data samples, use Python in formulas to calculate KPIs, and get a real‑time preview of the result. If the model changes, they adjust the formulas or relationships with a few clicks. This agility is hard to achieve with a traditional BI tool where each change may require SQL code, deployments, etc. Grist lets business users take back control over building their own tracking tools, without waiting for a ready‑made solution from the IT department. In this it approaches the spirit of “self‑service BI”, but goes further: it is not only self‑service in consumption and report creation, but also in application creation (since you can manage the source data directly inside).
Naturally, you need to be aware of Grist’s limits in BI: it is not a tool optimised for millions of rows or complex OLAP cube calculations. For very advanced analyses, or when data come from multiple disparate systems in real time, the big names on the market (Power BI, Tableau, etc.) have unmatched features. But one does not prevent the other. Grist can complement an existing BI ecosystem by serving as a local base for certain reference data, or by feeding a BI tool downstream via scheduled exports. The reverse is true too: a warehouse export could be loaded into Grist to give non‑technicians a more user‑friendly access to raw data that they can manipulate at will.
Ultimately, positioning Grist in an organisation’s BI comes down to recognising that between individual spreadsheets and industrial BI, there is room for an intermediate solution. This solution offers enough structure and analytical capacity to inform decisions (charts, aggregations, dynamic filters), while remaining simple enough to be managed by the operational staff themselves. In the age of no‑code/low‑code, Grist embodies this trend applied to data: giving end users the power to build their own analysis tools, without sacrificing the reliability of the underlying structure.
Example of a small dashboard built in Grist. Here, a sports database: on the left, the list of teams; top right, a detailed record of the selected team; bottom, the players filtered by team and an interactive chart of positions. This type of combined view shows how Grist can serve as a small business application and analysis tool, all in one.
Open source and data sovereignty: the strategic advantage of Grist.
Beyond feature considerations, choosing Grist is part of a broader choice in favour of open source and digital sovereignty. For a professional or non‑technical decision‑maker, these notions may seem abstract, but they have very concrete repercussions.
Data sovereignty means that you keep control of your information, its location and who accesses it. With an open‑source tool like Grist, you can host your data wherever you want – on a server in Canada, in Europe, in your own datacentre – and thus comply with local regulations (e.g., GDPR in Europe) and the confidentiality requirements of your clients or partners. Unlike American cloud solutions where data travels through foreign servers, a self‑hosted Grist ensures your data stays with you. From a security standpoint, this reduces the attack surface: no vulnerable third‑party account, no risk of a cloud service scanning or monetising your data. Grist Core was designed with this in mind from the start: “can be installed locally without requiring a user account, no telemetry enabled by default, data entirely under your control”. These are guarantees that are hard to obtain with proprietary software.
Open source also brings transparency. Grist’s code is public, so it can be audited by anyone who takes the time. Communities or even public bodies (such as ministries) can verify that there is no backdoor, contribute to fixing vulnerabilities, etc. This transparency creates a relationship of trust different from that with a closed vendor where one is forced to “take their word” on marketing promises. Indeed, the French administration did not miss the mark by supporting Grist: this meets the “growing concerns about data portability and autonomy, fundamental values of the project”, and for organisations concerned with security “this characteristic represents a decisive advantage”.
Another advantage is the absence of proprietary lock‑in. With Grist, if you want to stop tomorrow, you keep your data in a standard format (SQLite) and you can even continue using the software because it’s yours – the publisher cannot “shut down” Grist Core. By contrast, leaving a service like Airtable or Notion can be complex: incomplete export, specific functions lost, need to recreate the application elsewhere... By choosing a free solution, you invest in a long‑lasting tool whose evolution does not depend solely on a commercial strategy, but on a broader community. Grist Labs, the company behind the project, of course has an interest in keeping its product alive, but the open‑source code will outlive it no matter what, thus ensuring the durability of your investment.
Finally, choosing Grist can be part of a broader approach to digital sovereignty in your organisation. This means reducing dependence on proprietary software giants, encouraging local or community solutions, and taking back control over strategic tools. Without being “militant” at heart, this can be seen as a competitive advantage: more agility, potentially lower costs (no mandatory subscription), easier regulatory compliance, and the ability to finely adapt the tool to your needs (thanks to open source, your developers could add a specific feature if really necessary). It’s not about denigrating proprietary solutions – they have their place – but about giving choice and control back to the end user. As the comparison with Airtable highlights, being able to self‑host changes the game by eliminating external dependencies and offering total freedom of use.
In conclusion, Grist embodies the vision of a tool committed to user autonomy, without compromising efficiency. Without falling into a dogmatic discourse, it can be said that adopting Grist is not only a technical choice, but also a strategic and ethical choice for organisations concerned about their data.
Conclusion
Grist stands out as a unique player in the landscape of data management and lightweight Business Intelligence tools. Neither a simple spreadsheet nor an analytical behemoth, it brings the best of both worlds: the ease of use and flexibility of Excel, combined with the structure and power of a database, all in an open and modular solution. For businesses, SMEs, associations or communities looking for a modern tool to organise their information, collaborate in real time and gain insights from their data, Grist offers a credible alternative to proprietary platforms.
This comparative report has highlighted that Grist Core, the open‑source version, stands up to the big names in the sector on many aspects – with the unique advantage of digital sovereignty. Opposite it, tools like Airtable shine for their simplicity but can show their limits in terms of cost and data lock‑in. Power BI and Data Studio excel at visualising pre‑existing data, but do not offer the integrated management and editing environment that Grist provides. Everything of course depends on context and needs: Grist is not the universal answer to all use cases, but it brilliantly fulfils its mission in the segment for which it was designed.
For a non‑technical professional audience, Grist ultimately represents an exciting promise: “your data, your way” to paraphrase its philosophy. It is the possibility to create tailor‑made, scalable solutions yourself, without unnecessary code, and without fearing losing control of the tool or the data. In a world where data is a treasure and questions of digital trust are increasingly central, tools like Grist offer a breath of fresh air: they give users back power over their data while allowing them to innovate and collaborate effectively. In this sense, Grist is not just yet another piece of software, but the symbol of a new way of seeing advanced office tools – freer, more transparent, and user‑centric.
Sources: The information in this article comes from Grist’s official documentation and feedback from users and experts, as well as comparisons published in 2024–2025 on open‑source and no‑code alternatives. Specific quotations and excerpts are provided throughout the text to support each key point. You are thus invited to consult these sources to learn more and verify for yourself the veracity of the advanced features of Grist. We hope this dossier has shed light on Grist’s strengths and helped you consider how this tool could perhaps put an end to the chaos in your data… while giving you back control!