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DataMind Universe

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The whole OS. Two months. Free.

Every app, on your own servers, with your own data.

  • Your data stays on your servers On your servers
  • Installed in about 20 minutes 20-minute install
  • No card, no feature limits No card

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DataMind OS vs Databricks

Everything you build on Databricks. On your servers.

DataMind OS runs the ingestion, lake, warehouse, pipelines, governance, BI and AI agents teams build on Databricks, and adds Slides, Oda and one company price, on your own servers.

01Verdict

The short answer.

DataMind OS covers everything teams use Databricks for, and adds much more on top: DataPrism BI, Slides, Writeback and more than 20 AI agents, in one OS on your own servers at one company price.

Databricks today. Managed cloud data and AI platform (lakehouse) that runs on AWS, Microsoft Azure and Google Cloud.

  • On your servers.

    Installed on your own Linux servers in about 20 minutes, in any cloud or data center.

  • One OS, one login.

    Connectors, Lake, Warehouse, DataPrism BI, Slides and AI Minds share one set of access rules in the database.

  • Free builders and viewers.

    Report and dashboard builders, Mind builders, viewers and subscribers are free for an unlimited number of users.

02Side by side

DataMind OS and Databricks, row by row.

14 topics. Every Databricks fact cites a numbered source, checked October 2026.

DataMind OS compared with Databricks, checked October 2026
Topic DataMind OS Databricks
Where it runs On your own Linux servers, in any cloud or data center, physical or virtual. The browser Installer sets up DataMind OS in about 20 minutes on the recommended hardware, and your Lake, Warehouse, semantic models and reports stay on your servers. A managed cloud service on AWS, Azure and Google Cloud. Databricks runs the control plane in its own account; classic compute runs in your cloud account and serverless compute in Databricks' account. Databricks offers no edition you install and run on your own servers.1, 2
Pricing One company plan with every app and one Privileged seat included, priced on the pricing page. DataMind meters no compute, storage, queries or bandwidth; your server is billed by your own provider. Pay as you go, per second, in DBUs priced by compute type, with committed-use discounts. October 2026 list rates on Premium in AWS US East: $0.15 per DBU for classic jobs, $0.55 for classic all-purpose compute and $0.70 for serverless SQL. Classic compute adds a separate cloud VM bill.3, 4, 5
Who pays for seats Free for an unlimited number of users: report and dashboard builders, Mind builders, Oda users, viewers and subscribers. With 1,000 report developers and 10,000 viewers, not one of those seats costs anything. Only a Privileged seat (integrations, the data warehouse and access permissions) has a price, and the plan includes one. No per-seat fees for AI/BI; usage bills in DBUs. Genie One and Genie Agents are free for users through January 31, 2027, and Genie Code bills pay as you go beyond 150 free DBUs per user a month.6, 7, 8
Time to value About 20 minutes from a fresh Linux host to a running DataMind OS, with a demo semantic model and report ready to explore on day one. The two-month free trial runs the full OS on your own servers, on your own data. A serverless workspace starts in seconds, and the trial gives up to $400 of credits for 14 days. Databricks' own 2026 migration examples ran from about 8 weeks to 15 months.9, 10, 11
Connectors and ingestion 22 built-in source types: SQL Server, Postgres, Oracle, MySQL, MariaDB, ClickHouse, Snowflake, Redshift, BigQuery, Azure SQL, MongoDB, Firestore, Firebase Realtime Database, RabbitMQ, webhooks, S3, Athena, CSV, TSV, JSON, Parquet and Excel. Connect Any API has AI build a connector for any REST, OData or GraphQL API, and the custom connector agent writes and tests a Python connector for anything else. Eight Lake load patterns are settings, and there is no fee per connector or synced row. Lakeflow Connect lists more than 100 managed connectors for SaaS apps, databases, files and streams, on serverless compute, with 100 free DBUs a day per workspace for eligible sources. Auto Loader handles cloud files and Zerobus Ingest handles events.12, 13
Storage and SQL engine Lake and Warehouse tables live in ClickHouse on your servers, columnar and ZSTD-compressed, with each table's real compression ratio shown. Every chart, export and subscription queries current tables live, with no extracts to schedule. Each user gets a matching database account, so DataGrip, DBeaver, Excel and Power BI connect under the same row and column rules. Delta Lake tables by default, plus Unity Catalog managed Iceberg tables, in your object storage or Databricks default storage. SQL runs on SQL warehouses (Classic, Pro and Serverless) on the Photon engine, with Apache Spark for general compute.14, 15, 16
Transformation and warehouse modeling A warehouse that builds itself: Deploy writes each table's DDL, partitions and sort key, nine load patterns generate the load SQL for facts and dimensions, and change history is a switch on a dimension. Generate SQL with AI proposes each change in a diff, every load checks duplicate keys before it writes, and Test Run shows every insert, update and delete on real data before a table changes. Notebooks in Python, SQL, Scala and R, Lakeflow Spark Declarative Pipelines, the visual Lakeflow Designer, materialized views and streaming tables, dbt tasks and the Genie Code agent.17, 18
Orchestration Workflows order themselves from the dependencies the engine reads in your SQL, run independent steps in parallel, wait on other workflows through gates and refuse circular dependencies. Restarts rerun only unfinished steps, up to 10 automatic retries handle temporary errors, and any run replays on a timeline. Failure alerts go to Email, Slack, Discord or Google Chat. Lakeflow Jobs runs notebook, SQL, pipeline, dbt, dashboard and Power BI tasks, with if/else and for-each logic, triggered by schedules, file arrival or table updates.19
Governance and lineage Object, column and row rules compile into per-role database views, so the same limits hold in the SQL editor, DataPrism, Minds and external SQL tools, all in the one plan. Lineage writes itself from ClickHouse's own query tree, from sources through Lake and Warehouse to semantic models, Minds and Slides, filtered to what each viewer may see. One Audit button exports users, roles and effective permissions to Excel. Unity Catalog governs tables, volumes, models and AI services, with row filters, column masks and tag-driven ABAC policies, and automatic lineage down to column level for queries run on Databricks.20, 21
BI and the semantic layer DataPrism is in the plan: governed semantic models with measures and calculated columns written in SQL, 130 measure recipes, up to 50 tests per measure on live data, 15 visual types, bookmarks and row-level security. Report Builder AI builds a page from a description or a screenshot in minutes, and Custom Visual AI writes any other visual on the VDK, the Visual Development Kit. AI/BI Dashboards and Genie, with no license fee beyond DBU usage. Metrics live in Unity Catalog metric views, defined in YAML with SQL expressions, and Power BI, Tableau and Sigma can query them.6, 22
AI agents More than 20 purpose-built AI agents share more than 250 tools across the OS. Minds answer business questions by writing and running SQL on your governed tables, each step shown as a card with its SQL and result, under the Mind's own column grants or as the asking user. Lake Builder and Warehouse Builder do the data engineering in chat under approval modes, and Model AI, Slides AI and Custom Visual AI build models, decks and visuals. Genie One for business users, shareable Genie Agents, Genie Code for data and ML work in notebooks, SQL and pipelines, and Agent Bricks for custom agents, governed by Unity Catalog.23, 8, 24
AI models and data handling Kartlos Premium and Kartlos Standard are built in, with 85M Premium and 850M Standard tokens a month in the plan, and admins can allow more models from a curated catalog. Every model and embedding call routes only to zero-data-retention endpoints, EU routing is one setting and the default for new companies, columns marked as personal data reach a model only as tokens, and the AI audit trail is stored in your own database. Partner-powered assistive features use Azure OpenAI, OpenAI or Anthropic through zero-data-retention endpoints, or Databricks-hosted open models when that setting is off. Assistive features follow Databricks Geos for data residency, and data sent to models respects Unity Catalog permissions.23
Decks and delivery Slides is in the plan: Slides AI builds and edits decks, a Mind turns a chat into a deck, and charts, tables and text bind to live SQL. Decks export to PowerPoint with native, editable charts. Reports export to PDF and PowerPoint, email subscriptions deliver them under each recipient's own rows, and any visual streams its full result, even a billion rows, as CSV or TSV. Genie One drafts documents with citations that export to PDF and accepts PowerPoint files as input. AI/BI dashboards can be embedded in business applications.25, 6
Team to run it One OS to run, operated from the browser: the Installer and the admin screens handle service status, updates and container logs, memory limits are sized to the host automatically, and a named release arrives every month. Builder agents and connector wizards turn loading and modeling into settings, so SQL is the core skill. Teams typically staff data engineers in SQL and Python or PySpark, cloud engineers for networking and identity on classic workspaces, Unity Catalog administrators and DBU cost management. Large rollouts commonly use partners or system integrators.26, 27

Checked . Sources at the foot of the page.

03Further

Where DataMind OS goes further.

All of it in the same plan, on the same servers, under the same rules.

  1. A warehouse that builds itself

    Deploy writes each table's DDL, partitions and sort key, nine load patterns write the load SQL, and Test Run shows every insert, update and delete on real data before a table changes.

  2. DataPrism BI

    Governed semantic models with measures and calculated columns in SQL, up to 50 tests per measure on live data, and Report Builder AI, which builds a page from a screenshot in minutes.

  3. Slides

    Slides AI builds and edits decks whose charts, tables and text bind to live SQL, and decks export to PowerPoint with native, editable charts.

  4. AI Minds on governed tables

    Minds answer business questions by writing and running SQL on your own ClickHouse, every step shown with its SQL and result, and Execute as User applies each person's own rows.

  5. Writeback

    Rows from a Lake table, a Warehouse table or your own SQL go into MSSQL, Postgres, ClickHouse, Oracle, MySQL, MariaDB or BigQuery, or as JSON messages to RabbitMQ, on a schedule.

  6. Free builders and viewers

    Report and dashboard builders, Mind builders, Oda users, viewers and subscribers are free for an unlimited number of users: 1,000 report developers and 10,000 viewers cost nothing.

04Switch

Switch from Databricks.

Install DataMind OS beside Databricks, load the same sources, move pipelines and dashboards one at a time, and keep Databricks running until the last workload has moved.

  1. Day one

    Install DataMind OS on a Linux server in any cloud or data center, in the same cloud and region as your Databricks workspace if you like, in about 20 minutes. A demo semantic model and report are ready to explore, and the two-month free trial runs on your own servers.

  2. Sources

    The databases and files that feed Databricks connect straight to the DataMind Lake: SQL Server, Postgres, Oracle, MySQL, MariaDB, Snowflake, BigQuery, Redshift, MongoDB, S3 and Parquet, CSV, JSON and Excel files, through guided wizards with a connection test. SaaS APIs such as Salesforce come in through Connect Any API, and Batch Edit sets load patterns and schedules for hundreds of tables in one grid.

  3. Data already in Databricks

    Tables in Databricks come in through Connect Any API or a custom connector the agent writes and tests, and Parquet or CSV files your jobs already write to S3 load through the S3 connector.

  4. Pipelines

    Spark SQL and dbt models become Warehouse transformations in ClickHouse SQL: Generate SQL with AI rewrites each one in a diff, Import from SQL builds the columns, nine load patterns write the load SQL, and Test Run proves each load on real data. Workflows then order themselves from the dependencies.

  5. Dashboards and models

    Each AI/BI or Power BI page comes over from its screenshot: Report Builder AI rebuilds it on a DataPrism semantic model in minutes, Model AI writes the measures in SQL from plain language, and Custom Visual AI rebuilds a bespoke visual from its picture.

  6. Agents

    Genie Agents become Minds: link the tables, teach them with training cards, and switch on Execute as User so one Mind serves a whole department, each person under their own rows.

  7. In parallel

    Databricks keeps running while workloads move. Power BI reports can read the DataMind tables live through Universe, with DirectQuery or an ODBC import, each person under their own roles and row rules, so every team keeps working while pages move.

Q and A

Questions, answered.

What teams ask before they move from Databricks.

Is there a self-hosted alternative to Databricks?

Yes. DataMind OS installs on your own Linux servers, in any cloud or data center, in about 20 minutes, and runs ingestion, the lake, the warehouse, pipelines, governance, BI and AI agents in one OS. Databricks always runs its control plane in its own account.

How does DataMind OS pricing compare with Databricks pricing?

DataMind OS is one company plan, with every app, one Privileged seat and 85M Kartlos Premium and 850M Kartlos Standard tokens a month included, and DataMind meters no compute, storage or queries. The plan and the price of an additional Privileged seat are on the pricing page. Databricks bills DBUs per second by compute type, plus cloud VMs on classic compute.

Who needs a paid seat in DataMind OS?

Only the people who build integrations, the data warehouse and access permissions, and the plan includes one of those Privileged seats. Everyone else is free, for an unlimited number of users: report and dashboard builders, Mind builders, Oda users, viewers and subscribers.

Can we bring our Databricks pipelines and dashboards over?

Yes. Your sources connect straight to the DataMind Lake, Spark SQL and dbt models become Warehouse transformations with Generate SQL with AI, and Report Builder AI rebuilds each dashboard page from its screenshot on a DataPrism semantic model. Data already in Databricks comes in through Connect Any API or a custom connector the agent writes.

Do we still need Power BI or Tableau on top?

No. DataPrism is in the plan, and it has everything Power BI has, and more: measures and calculated columns in SQL instead of DAX, print-ready pages through Export to PDF and scheduled PDF subscriptions, a native streaming download of any visual, a billion rows as CSV or TSV, .dataprism report files, and custom interactive visuals that Custom Visual AI writes on the VDK.

How does DataMind OS handle AI and our data?

Minds run their SQL on your own ClickHouse under their own column grants or as the asking user. Every model call routes only to zero-data-retention endpoints, columns marked as personal data reach a model only as tokens, EU routing is one setting, and the AI audit trail is stored in your own database.

How do we try DataMind OS beside Databricks?

Start the two-month free trial. It runs the full DataMind OS on your own servers, installed in about 20 minutes, with a demo semantic model and report on day one, while Databricks keeps running until you choose what moves.

05Sources

Where the facts come from.

Checked . Product names are trademarks of their owners.

  1. docs.databricks.com/aws/en/getting-started/high-level-architecture
  2. community.databricks.com/t5/get-started-discussions/databricks-on-premises-or-in-private-cloud/m-p/109432/highlight/true
  3. databricks.com/product/pricing
  4. owox.com/blog/articles/databricks-pricing
  5. flexera.com/blog/finops/databricks-pricing-guide
  6. databricks.com/product/business-intelligence
  7. docs.databricks.com/aws/en/release-notes/product/2026/august
  8. docs.databricks.com/aws/genie
  9. databricks.com/try-databricks
  10. databricks.com/blog/serverless-workspaces-azure-databricks-now-generally-available
  11. databricks.com/blog/data-lakehouse-better-data-warehouse-2026-benchmarks-and-proof
  12. databricks.com/product/data-engineering/lakeflow-connect
  13. docs.databricks.com/aws/en/release-notes/product/2026/october
  14. docs.databricks.com/aws/en/release-notes/product/2026/may
  15. databricks.com/product/databricks-lakehouse
  16. docs.databricks.com/aws/en/compute/sql-warehouse/warehouse-behavior
  17. docs.databricks.com/aws/en/ldp/concepts/where-is-dlt
  18. databricks.com/blog/whats-new-lakeflow-designer-october-2026-roundup
  19. docs.databricks.com/aws/en/jobs/configure-task
  20. docs.databricks.com/aws/en/data-governance/unity-catalog/data-lineage
  21. docs.databricks.com/aws/en/release-notes/product/2026/april
  22. docs.databricks.com/aws/en/metric-views
  23. docs.databricks.com/aws/en/databricks-ai/databricks-ai-trust
  24. databricks.com/blog/agent-bricks-dais-2026
  25. docs.databricks.com/aws/en/ai-bi/release-notes/2026
  26. docs.databricks.com/gcp/en/lakehouse-architecture/deployment-guide/network
  27. eesel.ai/blog/databricks-review
  28. databricks.com/blog/announcing-databricks-storage-ecosystem-governing-enterprise-data-estate-wherever-it-lives
  29. databricks.com/product/pricing/databricks-sql
  30. databricks.com/blog/databricks-visionary-gartnerr-magic-quadranttm-analytics-and-business-intelligence-platforms

Try it beside Databricks.

Two months, the whole OS, on your servers. Free.