Dataki vs Mode
A Mode alternative that doesn't wait for an analyst's SQL
Mode pairs a SQL editor with Python and R notebooks, reports, and datasets that non-analysts can explore visually; it has been part of ThoughtSpot since 2023. Dataki targets the request that reaches an analytics team in the first place: the question is asked in plain English, answered from the warehouse directly, and kept as a dashboard without an analyst writing the SQL.
Why Dataki?
- Business users ask in plain English, and Dataki writes the SQL instead of queueing the request for an analyst.
- The SQL is shown and editable with every answer, so analysts can review it.
- No dataset has to be published first: Dataki reads the schema and writes the query for the question asked.
- Priced on data sources and AI messages, not seats. Viewers are free.
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Where Mode stands
What it does well
- A SQL editor with reports built on the query results
- Python and R notebooks on the same results
- Datasets and Visual Explorer for exploring without code
- Scheduled reports, with email and Slack sharing
Where it gets in the way
- Reports start from SQL written in the editor
- Code-free exploration works from datasets an analyst has published
- AI Assist is turned on account by account, on request
- Paid plans are quoted after a demo rather than published
Dataki and Mode at a glance
What each one asks of you, what it keeps, and where your data is queried.
| Row | DATAKI | Mode |
|---|---|---|
| How you ask a question | DATAKI Type the question in plain English. Dataki writes the SQL, runs it and draws the chart, and the SQL is shown with the answer for you to edit and re-run. | Mode Write SQL in the editor and extend it in Python or R. AI Assist writes and fixes SQL from comments. |
| Who can build | DATAKI Everyone on the team, whether or not they write SQL. Anyone can view a dashboard for free. | Mode Analysts write SQL and build reports; business users explore published datasets and reports. |
| What you keep | DATAKI A live dashboard on a permanent link that refreshes on its own, with filters and a date range. | Mode A report of queries, charts and notebooks, shared or sent on a schedule. |
| Where the data is queried | DATAKI On your database or warehouse, through a read-only connection, when the question is asked or the dashboard refreshes. Uploaded CSV and Excel files are snapshots. | Mode SQL runs against your warehouse. Datasets are cached in Mode's own engine for exploration. |
| Setup before the first chart | DATAKI Connect a source with a read-only user. No modelling layer: optional notes per source (metric definitions, joins, column warnings) that the model reads before it writes SQL. | Mode Connect a warehouse. An analyst writes the queries, or publishes the datasets others explore. |
| AI assistants and MCP | DATAKI A remote MCP server on every plan: Claude, ChatGPT, Cursor and VS Code query your sources and save dashboards, and Claude draws the answers as charts. Credentials never reach the model. | Mode AI Assist for SQL in the editor, enabled per account on request. |
| Embedding | DATAKI A <dataki-dashboard> web component, a React component or an iframe, with each of your customers limited to their own rows. | Mode Internal embeds, and white-label embeds through signed URLs. |
| Pricing model | DATAKI By data sources and AI messages, not seats. Everyone on the team can build, and viewers are free. | Mode Studio is free for individuals; Pro and Enterprise are quoted after a demo. |
Which one to choose
Choose Mode if…
- Your analysts work in SQL and want Python or R on the same results.
- You want curated datasets that business users explore by dragging fields.
- You already run ThoughtSpot, or plan to.
- Your warehouse is one Dataki does not connect to.
Choose Dataki if…
- Most requests to your analysts are questions a single sentence could ask.
- You want the answer kept as a dashboard without someone building a report by hand.
- You want Claude, ChatGPT or Cursor to query your warehouse through a read-only, governed connection.
- You want pricing that does not grow with the number of people reading the dashboards.
Questions about Mode and Dataki
- Is Dataki a replacement for Mode?
- For the requests that reach your analysts, it can be. In Dataki the person with the question asks it in plain English, Dataki writes and runs the SQL against the warehouse, and the answer is kept as a live dashboard. Mode remains the better tool for analysts' own work in SQL, Python and R.
- Does Mode have AI?
- Yes. Mode's AI Assist generates SQL from natural-language comments in the editor, fills in joins and conditions, and fixes syntax. Mode turns it on account by account, on request. Dataki writes the whole query from a plain-English question and shows it for review.
- Can business users explore data in Mode without SQL?
- Yes, from datasets. An analyst writes SQL once and publishes it as a dataset, and others explore it with Visual Explorer: dragging fields, filtering and changing chart types. In Dataki, the business user asks the question and Dataki writes the SQL, so no dataset has to exist first.
- Can Dataki connect to the same warehouse as Mode?
- If it is one Dataki reads, yes. Dataki connects to Google BigQuery, PostgreSQL, MySQL, Amazon Redshift, Supabase, Google Sheets and uploaded CSV or Excel files, always through a read-only connection. It does not connect to Snowflake, Databricks or SQL Server.
Try Dataki alongside Mode
Connect one data source on the free tier and ask it a question. It takes a few minutes, and dashboards you keep are free to share with as many people as you like.