Hex
Hex is rebuilding analytics around an agent — now an MCP client that pulls context from anywhere.
Comparison · Analytics
Mode Analytics vs Count
A side-by-side editorial comparison of Mode Analytics and Count — release velocity, themes, recent moves, and the top alternatives to consider.
Mode Analytics vs Count: at a glance
| Feature | Mode Analytics | Count |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 2.5 | 6.3 |
| Sparks · 30d | 0 | 1 |
| Top themes | business intelligence, spreadsheet ui, cross-source joins, sql editor | agentic-analytics, mcp, public-api, warehouse-connectors |
| Last editorial update | 1mo ago | 11d ago |
| Website | — | Visit → |
What is Mode Analytics?
Mode is converging spreadsheets, SQL, Python, and cross-source joins into one analyst surface.
Mode is making its core report editor more flexible and analyst-friendly: a native Excel-style spreadsheet mode with 70+ formulas alongside SQL and Python, a Data Mashup capability for cross-warehouse joins without ETL, a substantially overhauled SQL editor, shareable filtered URLs, and granular per-viz downloads in white-label embeds. Admin-side governance has kept pace with admin-managed refresh schedules and automated data retention policies.
What is Count?
Count is turning its BI canvas into a governed, agent-operated analytics platform.
Count is a data-canvas analytics tool reorganizing itself around an AI agent. In two months it shipped a full public REST API and hosted MCP server (governed agent access via OAuth and service accounts), a major agent upgrade that lets the agent read and edit the entire canvas and answer from Slack, and the ability to plug external MCP servers (Linear, HubSpot, Stripe, Slack, Drive) into the agent. Around the agent it keeps broadening warehouse support—ClickHouse, Snowflake semantic models, OSI—alongside chart and UX polish.
Mode Analytics vs Count: editorial side-by-side
Mode Analytics
2.5ANALYTICS
Mode is converging spreadsheets, SQL, Python, and cross-source joins into one analyst surface.
◆ Current state
Mode is making its core report editor more flexible and analyst-friendly: a native Excel-style spreadsheet mode with 70+ formulas alongside SQL and Python, a Data Mashup capability for cross-warehouse joins without ETL, a substantially overhauled SQL editor, shareable filtered URLs, and granular per-viz downloads in white-label embeds. Admin-side governance has kept pace with admin-managed refresh schedules and automated data retention policies.
◆ Where it's heading
Mode is doubling down on the 'one workspace for SQL, Python, and spreadsheets' positioning at a moment when most BI tools are picking a lane. The cross-source Data Mashup is the more strategic bet — it positions Mode as a thin governance/analysis layer sitting above multiple warehouses, useful in shops with fragmented data infrastructure. White-label embedding work hints at continued investment in the analytics-for-customers segment.
◆ Prediction
Expect AI/copilot features to layer onto the new SQL editor and spreadsheet surfaces (natural-language query, formula suggestion), and Data Mashup to graduate from invite-only to GA with notebook-output and CSV/Excel sources following. White-label embeds are a likely target for richer customer-facing interactivity given Mode's product-analytics-embed customer base.
Count
6.3ANALYTICS
Count is turning its BI canvas into a governed, agent-operated analytics platform.
◆ Current state
Count is a data-canvas analytics tool reorganizing itself around an AI agent. In two months it shipped a full public REST API and hosted MCP server (governed agent access via OAuth and service accounts), a major agent upgrade that lets the agent read and edit the entire canvas and answer from Slack, and the ability to plug external MCP servers (Linear, HubSpot, Stripe, Slack, Drive) into the agent. Around the agent it keeps broadening warehouse support—ClickHouse, Snowflake semantic models, OSI—alongside chart and UX polish.
◆ Where it's heading
Count is building toward analytics where agents are first-class operators: a governed API/MCP layer for access, an agent that drives the canvas end to end, external tool reach via MCP, and connection-level context so guidance is captured once and inherited. Governance—permissions, scopes, service accounts—is the enabling layer that makes agent access acceptable in real data stacks rather than a bolt-on.
◆ Prediction
Expect more connection- and warehouse-level context controls, a widening catalog of supported external MCP integrations, and deeper Slack-native agent workflows.
Alternatives to Mode Analytics and Count
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either Mode Analytics or Count.
Fulcrum
Fulcrum is in steady maintenance mode, polishing its field-mapping and mobile data-capture core.
Lightdash
Lightdash keeps sanding down the edges of self-serve BI, chart by chart.
Apify
Apify is rebuilding the Actor platform as MCP-first agent infrastructure.
Apache Superset
Duplicate Apache Superset row — same Helm-chart packaging feed, no distinct product signal
Apache Superset
Superset's public feed is all Helm-chart packaging — the 6.x product work sits behind release votes
See all Mode Analytics alternatives → · See all Count alternatives →
Recent activity from Mode Analytics and Count
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 15d agoCountConnect external MCP servers to the Count agent ⚡
- 29d agoCountDashed lines
- 1mo agoCountNew workspace home
- 1mo agoCountClickHouse support
- 1mo agoMode AnalyticsNative spreadsheet mode lands in Mode reports ⚡
- 2mo agoCountMajor Count agent upgrade: edits any cell, runs in Slack ⚡
- 2mo agoCountPublic API and MCP server ⚡
- 4mo agoMode AnalyticsWhite Label Embeds : Per-Visualization Data Downloads
- 4mo agoMode AnalyticsData Mashup enables cross-source SQL joins in one report ⚡
- 4mo agoMode AnalyticsNew and Improved SQL Editor
- 7mo agoMode AnalyticsIntroducing Shareable Report Views
- 8mo agoMode AnalyticsImport Notebook files directly
Frequently asked questions
What is the difference between Mode Analytics and Count?
They serve adjacent needs but don't currently overlap on shipped themes. Count is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is Mode Analytics better than Count?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Count is currently shipping more aggressively (velocity 6.3 vs 2.5), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to Mode Analytics?
Top Mode Analytics alternatives in Analytics are ranked by recent ship velocity. Browse the "Mode Analytics alternatives" section above for the current picks, or visit /alternatives/mode for the full list with editorial commentary on each.
What are the best alternatives to Count?
Top Count alternatives in Analytics are ranked by recent ship velocity. Browse the "Count alternatives" section above for the current picks, or visit /alternatives/count for the full list with editorial commentary on each.