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Comparison · Analytics

Count vs Keboola

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

Shared themes:mcp

Count vs Keboola: at a glance

FeatureCountKeboola
SectorAnalyticsAnalytics
Velocity score6.37.5
Sparks · 30d02
Top themesagentic-analytics, mcp, public-api, warehouse-connectorsdata-platform, ai-agents, mcp, etl
Last editorial update3mo ago1d 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 Keboola?

Keboola's Kai AI assistant hits GA, completing the pivot from data platform to AI-native pipeline orchestration layer.

Keboola's Kai AI assistant is now generally available for multi-tenant contracted customers, marking the formal transition from experimental feature to production-ready product. The platform is simultaneously navigating Snowflake's forced password authentication deprecation — a platform-level forcing function requiring customer migrations before September 7. Recent work also includes the MCP server gaining unified cross-project authentication, which enables AI coding assistants to act as first-class operators across a full Keboola stack.

Read the full Keboola trajectory →

Count vs Keboola: 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.

K
Keboola
ANALYTICS
7.5

Keboola's Kai AI assistant hits GA, completing the pivot from data platform to AI-native pipeline orchestration layer.

◆ Current state

Keboola's Kai AI assistant is now generally available for multi-tenant contracted customers, marking the formal transition from experimental feature to production-ready product. The platform is simultaneously navigating Snowflake's forced password authentication deprecation — a platform-level forcing function requiring customer migrations before September 7. Recent work also includes the MCP server gaining unified cross-project authentication, which enables AI coding assistants to act as first-class operators across a full Keboola stack.

◆ Where it's heading

Keboola is building toward a model where AI agents can autonomously manage the data pipeline lifecycle. The MCP server's unified auth is a signal: the target is a world where a developer's coding assistant can browse, create, and modify Keboola pipelines without a human navigating the UI. Kai GA and the MCP expansion are the same thesis from two directions — AI as interface, not AI as feature. Branched storage expansion to BigQuery and Flows improvements in the background are the operational stability layer those agents will depend on.

◆ Prediction

Kai gaining the ability to create and modify Flows, and the MCP server expanding its coverage to transformation and workspace management, are the two most visible next moves. The Branched Storage on BigQuery release is a prerequisite for Branches 2.0 approval workflows, which would give Kai a way to propose and commit pipeline changes with human review gates.

Alternatives to Count and Keboola

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 Keboola.

See all Count alternatives → · See all Keboola alternatives →

Recent activity from Count and Keboola

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

  1. 1d agoKeboolaKai is Now Generally Available (Multi-Tenant, Contracted Customers)
  2. 6d agoKeboolaMigrate Snowflake Workspaces from Password to Key Pair Auth
  3. 22d agoKeboolaKeboola MCP: Log In Once, Work Across Every Project
  4. 27d agoKeboolaPython 3.10 Deprecation for Streamlit Apps (September 2026)
  5. 1mo agoKeboolaFlows: New Condition Operators and Run Selected Tasks
  6. 1mo agoKeboolaBranched Storage on BigQuery
  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 Keboola?

Both compete on the same themes — mcp — within Analytics. Keboola is currently shipping more aggressively (velocity 7.5 vs 6.3), with 2 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 Count better than Keboola?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Keboola is currently shipping more aggressively (velocity 7.5 vs 6.3), with 2 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 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 Keboola?

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