In Mode
You're an analyst or data team building reports and dashboards over a warehouse.
Comparison
nlqdb vs Mode
Pick Mode if you're a data team that wants a SQL editor with connected Python/R notebooks and shareable reports over your existing warehouse. Pick nlqdb if you're building a product or agent that needs English-to-SQL over a database it provisions — embeddable, API-first, with every write diff-previewed.
The same goal, two ways.
> weekly active users by signup cohort for the last 6 months
In your HTML
<nlq-data goal="weekly active users by signup cohort for the last 6 months"></nlq-data>A grouped, time-bucketed query nlqdb answers as SQL over the database your app owns — the live data layer your product queries, not a report an analyst schedules.
What's different
Four dimensions that decide it
| Dimension | nlqdb | Mode | Note |
|---|---|---|---|
| Owns the database (provisions + migrates) | Mode connects to your existing warehouse; it doesn't provision or own a database your app writes to. | ||
| Natural-language data questions | Mode's AI now arrives via ThoughtSpot Sage (NL search over Mode Datasets) post-acquisition; nlqdb compiles SQL from English against a Postgres it owns. | ||
| Embeddable answer element + SDK + API | Mode embeds published reports/dashboards; nlqdb ships `<nlq-data>`, an SDK, and an HTTP API to query a database your product owns. | ||
| MCP server (agent-callable) | Mode is a notebook + reporting surface analysts log into, not an agent-callable MCP backend; nlqdb's `nlqdb_query` materialises Postgres on first reference. |
Show 6 more rows
| Dimension | nlqdb | Mode | Note |
|---|---|---|---|
| Charts, dashboards + shareable reports | Mode builds charts, dashboards, and scheduled live reports; nlqdb returns typed result rows you render in your own UI. | ||
| Python / R notebook cells | Mode is a SQL editor plus connected Python + R notebooks; nlqdb's output contract is SQL plus rows, not a notebook runtime. | ||
| Scheduled runs + threshold alerts | Mode schedules query runs and fires webhook/threshold alerts; nlqdb answers a query per request, not on a recurring report schedule. | ||
| Auto-migration via NL ('add a column for tags') | |||
| Destructive-op diff preview before apply | Mode queries and reports; it doesn't manage your schema. nlqdb previews writes and DDL before applying. | ||
| Connects to many existing warehouses | Mode reads Snowflake/BigQuery/Redshift/Postgres and more; nlqdb provisions and queries its own Postgres rather than connecting to many warehouses. |
shipped · partial · not shipped
When to choose nlqdb
- You're embedding data answers in your product or agent, not authoring reports.
- An AI agent must provision and query its own database, callable over MCP.
- You ship one HTML element or an API, not a notebook an analyst drives.
- Writes and schema changes should be diff-previewed before they apply.
When to choose Mode
- You're an analyst or data team building reports and dashboards over a warehouse.
- You want a SQL IDE plus connected Python/R notebooks in one workspace.
- You connect existing warehouses (Snowflake, BigQuery, Redshift), not provision a new database.
- You want scheduled report delivery and threshold alerts to your team.
Questions buyers ask
- Can I use Mode and nlqdb together?
- Yes — they serve different stages. Mode is where an analyst explores a warehouse and publishes a report or dashboard; nlqdb is the database your product or agent queries in plain English at runtime. Use Mode for analysis and reporting, nlqdb for the data layer your app ships on.
- Does nlqdb build reports and notebooks like Mode?
- No. nlqdb returns typed result rows from SQL it compiles; it doesn't ship a SQL IDE, Python/R notebooks, charts, or scheduled reports. If a collaborative SQL + notebook workspace and shareable dashboards are the goal, Mode is the right shape; nlqdb's contract is the data, which you render in your own UI.
- Is Mode's AI the same as nlqdb's natural-language querying?
- Different jobs. Since the ThoughtSpot acquisition, Mode's AI surfaces as ThoughtSpot Sage — LLM-powered search over Mode Datasets for analysts. nlqdb compiles English into SQL against a Postgres it provisions and owns, returns typed rows, and diff-previews any write — built to be embedded in a product or called by an agent, not driven in a notebook.
- Mode connects to my warehouse — why provision a new database with nlqdb?
- Mode reads your existing Snowflake/BigQuery/Redshift/Postgres for analysis and reporting. nlqdb owns the database your app writes to: it provisions Postgres, migrates the schema via English, and diff-previews destructive writes. Connecting-to-read and owning-the-write-path are different jobs.
- Does Mode have an MCP server like nlqdb?
- No. Mode is a notebook and reporting platform analysts log into, not an agent-callable backend. nlqdb's MCP is database-shaped: `nlqdb_query` materialises a Postgres on first reference, so an agent can provision and query its own database rather than read an analyst's report.
Try nlqdb in 30 seconds
No sign-in. The anonymous database lasts 72 hours; adopt it with one click if you keep it.
Start with a goal →