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Comparison · Analytics

Holistics vs MotherDuck

Side-by-side trajectory, velocity, and editorial themes.

Holistics logo
Holistics
ANALYTICS
7.5

Holistics leans into analytics-as-code with agentic dev workflows and a Power BI migration path

◆ Current state

Holistics is a BI platform built around analytics-as-code, where models and dashboards are defined in its AMQL language and version-controlled in Git. Recent releases push on three fronts at once: competitive migration (a one-command Power BI importer), AI-native authoring (Claude Code setup skills and a conversational Ask AI), and steady breadth work like an Oracle connector and org-level GitHub App auth. The throughline is making the code-first workflow easier to adopt and operate.

◆ Where it's heading

The direction is to lower the switching cost from incumbent BI tools while betting that analytics teams will work through agents and code rather than point-and-click. Migration tooling and agentic setup skills both target the same friction: getting a team productive in Holistics fast. Parallel embed and dashboard-runtime polish (auto-run, KPI styling) point to a continued focus on the embedded-analytics use case.

◆ Prediction

Expect the migration story to extend to other incumbents and the agentic-development skills to deepen, given the back-to-back Power BI importer and Claude Code setup releases. Embedded-analytics controls look set to keep maturing.

M
MotherDuck
ANALYTICS
7.5

MotherDuck climbs from serverless DuckDB warehouse to an agent-operable data platform

◆ Current state

MotherDuck ships a dense, real release stream on two fronts: tracking DuckDB core (1.5.x, DuckLake, concurrent checkpoints) and building an agent-and-embed layer on top (Dives data apps, an MCP server, the MCP Dive Viewer now in ChatGPT and Claude Cowork). The latest notes add server-side Iceberg interop and a new pipelines product, Flights.

◆ Where it's heading

The product is moving up the stack from query engine toward a full data platform: pipelines (Flights), interactive apps (Dives, now GA), open-table-format interop (Iceberg, DuckLake), and broad connectivity via the Postgres endpoint (Looker, Retool, Drizzle, dbt Cloud, DBeaver). MCP-native access recurs throughout, treating AI agents as first-class users of the warehouse.

◆ Prediction

Expect Flights and Iceberg attach to graduate from Preview to GA, more Postgres-endpoint BI and tool integrations, and continued MCP/agent surface. This is grounded in the visible pattern of previews maturing and steady Postgres-endpoint and MCP investment.

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