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Comparison · Analytics

Count vs OpenHouse

A side-by-side editorial comparison of Count and OpenHouse — release velocity, themes, recent moves, and the top alternatives to consider.

Count vs OpenHouse: at a glance

FeatureCountOpenHouse
SectorAnalyticsAnalytics
Velocity score6.36.3
Sparks · 30d01
Top themesagentic-analytics, mcp, public-api, warehouse-connectorsiceberg, data-lakehouse, linkedin, open-source
Last editorial update3mo ago12h ago
WebsiteVisit →Visit →

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.

Read the full Count trajectory →

What is OpenHouse?

OpenHouse breaks ground on Iceberg views while tightening storage lifecycle and authorization

OpenHouse (LinkedIn's managed Iceberg tables service) is shipping at a rapid v0.5.x pace with multiple improvements per week. Recent work spans three areas: storage lifecycle management (native snapshot expiration with reference age defaults, orphan file reclamation), authorization hardening (routing RTAS operations through proper table privilege checks), and the first scaffolding for Iceberg view support (entityType discriminator, table-scoped HTS queries).

Read the full OpenHouse trajectory →

Count vs OpenHouse: editorial side-by-side

C
Count
ANALYTICS
6.3

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.

O
OpenHouse
ANALYTICS
6.3

OpenHouse breaks ground on Iceberg views while tightening storage lifecycle and authorization

◆ Current state

OpenHouse (LinkedIn's managed Iceberg tables service) is shipping at a rapid v0.5.x pace with multiple improvements per week. Recent work spans three areas: storage lifecycle management (native snapshot expiration with reference age defaults, orphan file reclamation), authorization hardening (routing RTAS operations through proper table privilege checks), and the first scaffolding for Iceberg view support (entityType discriminator, table-scoped HTS queries).

◆ Where it's heading

The entityType discriminator in v0.5.490 is the most directional move in this window — it creates the data model prerequisite for treating views as first-class entities alongside tables, something OpenHouse has not supported. Storage lifecycle work is converging on Iceberg-native mechanisms, reducing custom expiration logic. The post-commit operations framework in v0.5.492 is infrastructure that will allow OpenHouse to add downstream hooks (compaction triggers, notifications) without catalog coupling.

◆ Prediction

Iceberg view read support will arrive in the next several releases, building on the discriminator and HTS scaffolding now in place. The authorization model for views will be an open question — watch whether they reuse the table ACL path or introduce a parallel model.

Alternatives to Count and OpenHouse

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 Count or OpenHouse.

See all Count alternatives → · See all OpenHouse alternatives →

Recent activity from Count and OpenHouse

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 14h agoOpenHousev0.5.492: Add a generic bounded post commit operations framework (#729)
  2. 5d agoOpenHousev0.5.491
  3. 5d agoOpenHousev0.5.490: Add entityType discriminator and table-scoped HTS queries (#696)
  4. 7d agoOpenHousev0.5.489: Backfill history.expire.max-ref-age-ms with Snapshot Expiration (#708)
  5. 11d agoOpenHousev0.5.488: [RTAS] Use table privileges for replacement (#711)
  6. 12d agoOpenHousev0.5.487
  7. 3mo agoCountConnect external MCP servers to the Count agent
  8. 3mo agoCountDashed lines
  9. 4mo agoCountNew workspace home
  10. 4mo agoCountClickHouse support
  11. 5mo agoCountMajor Count agent upgrade: edits any cell, runs in Slack
  12. 5mo agoCountPublic API and MCP server

Frequently asked questions

What is the difference between Count and OpenHouse?

They serve adjacent needs but don't currently overlap on shipped themes. Count and OpenHouse are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is Count better than OpenHouse?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Count and OpenHouse are shipping at a similar cadence (velocity 6.3 vs 6.3, both within Sparkpulse's "active" band). For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

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.

What are the best alternatives to OpenHouse?

Top OpenHouse alternatives in Analytics are ranked by recent ship velocity. Browse the "OpenHouse alternatives" section above for the current picks, or visit /alternatives/openhouse for the full list with editorial commentary on each.