Mode

SQL plus Python notebooks plus dashboards; acquired by ThoughtSpot.

Reviewed by 7wData

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Publisher review

Mode Analytics was a SQL-first business intelligence platform built for data analysts who preferred writing queries over dragging visual builders. Founded in 2013 in San Francisco, Mode gained recognition for bridging the gap between data warehouses and business users by providing an integrated environment for SQL querying, Python and R analysis, and dashboard creation. In July 2023, ThoughtSpot acquired Mode for $200 million, and the platform's capabilities were absorbed into ThoughtSpot Analyst Studio, which became generally available in early 2025.

This marks a significant shift: Mode is no longer available as a standalone offering to new customers, and existing Mode users are now operating within ThoughtSpot's unified platform. What made Mode distinctive was its code-first philosophy—it prioritized giving data analysts a native SQL editor alongside integrated Python and R notebooks. Query results flowed directly into analysis environments without manual export, and outputs could be published as interactive dashboards.

The platform's performance was amplified by Helix, an in-memory data engine originally built on VoltDB and later upgraded to DuckDB, which allowed visual exploration of up to 10GB of data. Mode's customer base included major companies like Bloomberg, Shopify, Reddit, Lyft, Condé Nast, and Walmart, with the platform reporting 140% net dollar retention pre-acquisition. For new projects, Mode is effectively off the table; organizations evaluating its former use cases must now choose between migrating to ThoughtSpot Analyst Studio or selecting alternatives.

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How it works

  1. SQL editor with Python and R notebooks

    Native SQL editor with auto-completion and query history; results automatically load into Python or R notebooks without manual export.

  2. Helix in-memory engine (DuckDB-powered)

    In-memory data engine enabling fast visual exploration of datasets up to 10GB with sub-second response times for ad hoc analysis.

  3. Direct data warehouse integrations

    Native connectors to Snowflake, BigQuery, Redshift, Databricks, and other major cloud data warehouses.

  4. Interactive dashboards and visualization builder

    Drag-and-drop dashboard builder allowing analysts to publish query results and notebook outputs as shareable, interactive reports.

  5. Governed datasets for self-serve analytics

    Datasets layer enabling controlled self-service analytics while maintaining data governance and query efficiency post-ThoughtSpot integration.

  6. Query automation and alerting

    Schedule recurring queries for delivery and configure webhooks to trigger alerts based on data changes or thresholds.

Strengths and trade-offs

Strengths

  • Code-first design eliminated friction for analysts; SQL queries flowed directly into Python/R notebooks and dashboards without manual export steps.
  • Helix in-memory engine delivered sub-second response times for visual exploration, reducing expensive warehouse queries and improving iteration speed.
  • Clean, collaborative interface made sharing SQL-based analysis and notebooks straightforward for technical teams.

Trade-offs

  • No longer available to new customers after July 2023 acquisition; existing users were forced to migrate into ThoughtSpot Analyst Studio ecosystem.
  • Steep SQL learning curve and limited visual self-serve capabilities made the platform inaccessible to non-technical business users.
  • Enterprise pricing model lacked public transparency, ranging from $6,000 to $50,000+ annually, limiting accessibility for smaller teams.

Pricing context

Mode operated on an enterprise licensing model with no public pricing tiers. Quoted estimates ranged from $6,000 to $50,000 annually depending on seat count, usage, and feature tier. The platform offered a free "Mode Studio" tier with limited computational resources (4GB RAM, 1 CPU) for Python notebooks and access to public datasets.

Mode's pricing was never transparent; prospective customers required direct sales engagement. Following the July 2023 ThoughtSpot acquisition, Mode ceased operating as an independent product, and new analytics workloads must now be evaluated against ThoughtSpot Analyst Studio's pricing or alternative platforms.

Frequently Asked Questions

What was Mode Analytics?

Mode Analytics was a SQL-first business intelligence platform founded in 2013 that let data analysts write queries and Python/R code directly, then publish results as interactive dashboards. It integrated SQL editing, notebooks, and visualization in one environment without manual export steps. Customers included Bloomberg, Shopify, and Reddit.

What happened to Mode Analytics after the ThoughtSpot acquisition?

In July 2023, ThoughtSpot acquired Mode for $200 million. Mode is no longer available as a standalone product to new customers. Existing users were migrated into ThoughtSpot Analyst Studio, which became generally available in early 2025. Mode's capabilities are now integrated into ThoughtSpot's unified platform.

Can I still use Mode Analytics?

Mode Analytics is no longer available to new customers as of July 2023. If you're an existing Mode user, you must migrate to ThoughtSpot Analyst Studio. If you need a similar SQL-first analytics platform, alternatives include Hex, Looker, Tableau, and Metabase. Organizations can no longer sign up for Mode directly.

What made Mode Analytics different from other BI tools?

Mode prioritized code-first design for data analysts. Its native SQL editor fed directly into Python and R notebooks without manual export, and outputs became interactive dashboards instantly. The Helix in-memory engine delivered sub-second response times on datasets up to 10GB, making iteration faster and reducing expensive warehouse queries.

How much did Mode Analytics cost?

Mode's pricing was enterprise-only with no public rates. Quotes typically ranged from $6,000 to $50,000+ annually depending on seat count, usage, and feature tier. A limited free 'Mode Studio' tier offered 4GB RAM and basic Python notebook access. Direct sales engagement was required for all pricing discussions.

What are the best alternatives to Mode Analytics?

Mode's primary alternatives are ThoughtSpot Analyst Studio (which absorbed Mode), Hex (Python notebooks), Looker (Google-backed BI), Tableau Cloud (visual analytics), and Metabase (open-source BI). ThoughtSpot Analyst Studio is the natural migration path for existing Mode users. Other options depend on whether you prioritize code-first capability, visual self-serve, or pricing accessibility.

Alternatives in this category

Integrations

Snowflake BigQuery Redshift Databricks

How Mode compares

Direct head-to-head against 3 competitors. Picked by 7wData.

This tool

Mode

Pricing
Mode operated on an enterprise licensing model with no public pricing tiers. Quoted estimates ranged from $6,000 to $50,000 annually depending on seat count, usage, and feature tier. The platform offered a free "Mode Studio" tier with limited computational resources (4GB RAM, 1 CPU) for Python notebooks and access to public datasets. Mode's pricing was never transparent; prospective customers required direct sales engagement. Following the July 2023 ThoughtSpot acquisition, Mode ceased operating as an independent product, and new analytics workloads must now be evaluated against ThoughtSpot Analyst Studio's pricing or alternative platforms.
Target
Mode Analytics was a SQL-first business intelligence platform built for data analysts who preferred writing queries over dragging visual builders.
Deployment
cloud
Strength
Code-first design eliminated friction for analysts; SQL queries flowed directly into Python/R notebooks and dashboards without manual export steps.
Watch for
No longer available to new customers after July 2023 acquisition; existing users were forced to migrate into ThoughtSpot Analyst Studio ecosystem.

Hex

Pricing
Free Community tier. Professional $36/editor/month. Team $75/editor/month. Enterprise custom. Compute billed separately on all paid plans.
Target
Data analysts and data scientists needing SQL plus Python and R notebooks in one shared workspace.
Deployment
SaaS
Strength
SQL queries flow directly into Python and R notebooks, outputs publish as interactive apps without exporting or switching tools.
Watch for
Compute (GPUs, larger machines) billed separately from editor seats, total spend escalates well beyond the headline per-seat price.

Looker

Pricing
Custom/Contact sales. Starts around $60,000/year. Viewer seats approximately $400/year each. Mid-market typically $80,000-$150,000+/year.
Target
Enterprises needing a version-controlled semantic layer managed centrally by a dedicated data engineering team.
Deployment
SaaS (Google Cloud)
Strength
LookML semantic layer enforces shared metric definitions across all dashboards and downstream tools organization-wide.
Watch for
LookML requires dedicated engineering headcount. Analyst estimates put 40-60% of total Looker spend on modeling and maintenance, not licensing.

Metabase

Pricing
Open source free (AGPL, self-hosted). Starter $100/month (5 users). Pro $575/month (10 users). Enterprise median ~$39,000/year.
Target
Teams wanting SQL-based BI without a large enterprise contract, including engineering teams comfortable self-hosting.
Deployment
SaaS or self-hosted open source
Strength
AGPL open-source build ships with 20-plus database connectors and unlimited dashboards at zero license cost for self-hosted teams.
Watch for
SSO, row-level security, and audit logs are locked to paid tiers. The open-source build omits all three by design.

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Sources

Reporting on this tool draws on these publicly available sources.

  1. www.thoughtspot.com — Acquisition completion date (July 19, 2023), deal size ($200M), strategic rationale, and integration timeline (Analyst Studio GA in early 2025)
  2. techcrunch.com — Mode's customer base (Bloomberg, Shopify, Reddit, Lyft, Condé Nast) and strategic positioning as code-first platform for data analysts
  3. www.capterra.com — User-reported strengths (SQL-based querying, easy sharing, fast performance) and weaknesses (steep learning curve, UI complexity, expensive pricing)
  4. www.modern-datatools.com — SQL-first approach, Python/R integration, Helix in-memory engine, and limited appeal to non-technical users versus Tableau/Power BI
  5. mode.com — Helix engine evolution from VoltDB to DuckDB, performance improvements in query execution and visual data exploration
  6. dashboardfox.com — Post-acquisition status (no longer standalone), missing row-level security, white-label limitations, and implications for existing customers