6 Palantir alternatives for mid-market teams

Palantir showed you how connected data could improve reporting and power internal apps, but the quote exceeded your budget. You still need that work done. Palantir alternatives to compare include Databricks, Permute, Snowflake, Dataiku, Microsoft Fabric, and a DIY Lovable + Supabase build. Compare what each option costs to get working and who will keep it running.

Permute publishes this comparison and sells connected business data, custom apps, and AI agents with implementation support. The options below cover different ways to get the work done: hire engineers, engage a consulting firm, or buy software with delivery and support included. Existing tools and the people available to maintain them should shape your shortlist.

Six Palantir alternatives at a glance

Compare the report or app you need, the full cost, and who will build and support it. Use these suggested fits to make a shortlist, then compare the implementation work described below.

1. Databricks: a data and AI development platform

Best fit: You have engineers building data pipelines, analytics, and AI products. Databricks combines storage, processing, analytics, and AI work in its lakehouse architecture. It supports SQL and Python work alongside batch and streaming data processing. Consider it when your team needs that development environment across several projects.

What you build: If you lack a data engineer, budget to hire one or engage a consulting firm. They need to connect sources, build data pipelines, and turn business rules into reports and app code. Databricks lists consulting and implementation partners for this work. Include ongoing maintenance: a renamed source field can break a pipeline and affect every report using it.

Pricing: Databricks offers pay-as-you-go usage and committed-use contracts. Its pricing page says storage, networking, and related costs vary by service and cloud provider. Add engineering salaries or consulting fees to the software and cloud bill. Ask for a budget that covers deployment, source changes, and support after launch.

2. Permute: reporting and apps with managed delivery

Best fit: You want a job-cost report, an inventory review, or a property dashboard, and need someone to connect the records and build it. Permute combines software with engineering support. We connect approved sources, match records across them, and resolve differences using rules your team approves. You can trace a reported number back to the records and calculations behind it.

What you build: We deliver the agreed reports or apps and maintain the connections covered by the engagement. Your finance or operations owner decides how the numbers should be calculated and handles business exceptions. The same prepared data can support more apps and supply permitted business context to Claude, ChatGPT, or Copilot. Your developers can also build their own interfaces; custom app hosting is in early access for compiled static frontends.

Pricing: A subscription with implementation and support priced to the agreed work. Permute can deliver a scoped reporting and app implementation at a fraction of the cost of a multimillion-dollar enterprise program. Typical implementations go live in weeks, starting with the sources and reports you need first. See Permute pricing and request a quote that includes the connections, app work, and maintenance.

3. Snowflake: reporting and AI on existing business data

Best fit: Your data is already in Snowflake, and you want reporting or AI to use it. Snowflake’s Cortex Agents can query structured data through Cortex Analyst and retrieve document information through Cortex Search. Snowflake manages the agent runtime, while access depends on privileges and the tools you configure.

What you build: Hire a data engineer or engage a consulting firm if you lack someone who can build and maintain the setup. Snowflake’s services partners offer implementation, migration, and consulting. Your builder still needs to connect sources, define calculations, and develop the reports or app. A margin question needs an agreed treatment of revenue and costs for the same reporting period.

Pricing: Snowflake uses consumption-based pricing. Include storage, compute, and the AI services used by your application. Cortex Agents can add charges for orchestration and its tools, so estimate repeated use as well as the first test. Add the engineering or consulting budget, including maintenance. Existing Snowflake data and working calculations can reduce the work needed for the first release.

4. Dataiku: shared development for analytics, models, and agents

Best fit: Analysts, data scientists, and developers need to work on analytics and AI projects together. Dataiku’s product overview describes visual and code-based data preparation, model development, and AI agents. It also includes controls for reviewing and managing that work. Consider it when coordinating several builders and projects is part of the requirement.

What you build: Assign people to prepare data, test models or agents, and release the finished work. Decide who approves changes and handles a failed job after launch. Visual tools can reduce the code needed for some steps, but your business still needs to define the calculations and check the outputs against known records.

Pricing: Request a production quote for the features, deployment, and support you need. Dataiku offers a hosted trial and Free Edition, which let you evaluate the software. Use the trial to check the work your team must do, then price the production setup and ongoing ownership before committing.

5. Microsoft Fabric: data preparation and Power BI reporting

Best fit: Your business uses Power BI and Microsoft analytics, and wants to build on that setup. Microsoft Fabric brings data ingestion, transformation, analytics, and reporting into one service. Its workloads use OneLake for shared storage. Existing reports and Microsoft experience can give your team a starting point.

What you build: Plan how source records get into Fabric, how reporting tables and calculations are prepared, and who can access them. Assign owners for the reports and capacity settings. If you already have a Power BI team, ask it to estimate that work before introducing a separate reporting system.

Pricing: Fabric sells compute capacity through pay-as-you-go and reservation options. Microsoft’s pricing page also describes storage charges and applicable Power BI licensing. Price the capacity and licenses your workload needs, then add development and support. Reusing existing reports helps only when their calculations and access rules meet the new requirement.

6. Lovable + Supabase: a DIY app with backend responsibilities

Best fit: You want to prototype an app and have a developer who can own the backend before it handles business records. Lovable’s Supabase integration can generate interfaces, database changes, and login flows. With your own Supabase project, you manage authentication settings, backups, and backend usage there. Lovable also documents that its signed-in browser testing requires its built-in backend; tests for your own Supabase project cover pages that don’t require signing in.

What you build: Login establishes identity; Supabase row-level security controls which records users can read or change. Someone must design those policies, test access across companies, and authorize privileged server calls that can bypass them. File downloads and exports need access checks too. Lovable says its security scans support, but don’t replace, a thorough security review.

The reporting work also needs an owner: connect ERP records, match customer and project IDs, and define which source wins when amounts disagree. Review schema changes and test recovery before launch. For a mid-market team without backend and security expertise, this creates a hiring or consulting requirement alongside the app subscription. Our Lovable + Supabase article walks through that work. Permute offers supported apps on governed business data for teams that want someone to deliver and maintain the setup.

Pricing: Lovable credits pay for building work, while your own Supabase project has separate backend billing. Include developer time, security review, and support when comparing that budget with a delivered app quote.

Palantir pricing and the mid-market budget

Palantir deals are often $10 million+. Its Q2 2026 business update reported 73 deals worth at least $10 million, measured as total contract value across government and commercial customers (including contract options). If the proposal is beyond your budget, scope the reporting and apps you need first, then compare the cost to deliver them.

For a Palantir Foundry pricing comparison, ask each provider to quote the same report or app, source connections, and support period. Include setup, subscriptions, usage charges, internal staff time, and changes after launch. A software price and a delivered application price pay for different work; put that work in the quote so you can compare the budgets.

Warehouse programs can also carry multimillion-dollar budgets. A Forrester study commissioned by Snowflake in April 2024 modeled $5.5 million in total costs over three years for a composite organization based on customer interviews. That figure covers a modeled enterprise program, including ongoing costs. Ask a data engineer or consulting firm to price your specific scope before treating a warehouse as the cheaper route.

Permute keeps the first implementation focused on a report or app your team will use. We connect its sources, build the agreed calculations, and deliver it with engineering support. You can add more reports using those same records and rules. That keeps the initial cost tied to a business need and gives your team one support path for the work we deliver.

How to choose a Palantir alternative

If you want someone to deliver and support business reporting or an app, compare Permute with a partner-built implementation on the other options. If you have engineers and need a data and AI development environment, include Databricks. For existing Snowflake or Power BI users, estimate what you can reuse before paying to rebuild it. Include Dataiku when several teams need to develop and review analytics or AI projects together. A Lovable + Supabase prototype can help test an interface, with a technical owner assigned to security and backend work before production.

Give each provider one report, its source records, and a known result to reproduce. Ask it to explain a disputed number and show what happens when a source stops updating. Include the people who will use the report in the review. Their questions will expose missing records and definitions that a feature checklist can miss.

Examples in construction, manufacturing, and real estate

Construction: Match posted accounting costs to projects and cost codes, then compare them with the approved budget and open commitments. Keep pending changes separate from approved changes and avoid counting invoiced work again as an open commitment. Our construction job-cost report shows the calculation. Ask the provider to reproduce it for one job before adding the rest.

Manufacturing: Bring orders, inventory, purchasing, and the demand plan into a sales, inventory, and operations planning (SIOP) review. Match item names and units before comparing quantities. The example below shows how a custom app can flag an unconfirmed receipt or shared line capacity and route it to the person responsible. The records are sample data.

Example workflow

Illustrative custom app · Sample data

Connected systems

Source records for this workflow

NetSuiteOrders, stock, and purchasing↗SAPProduction and cost records↗Excel / Google SheetsDemand plans and capacity inputs↗

Permute data foundation

Connected records, shared rules, source evidence, and governed access.

Custom application

Governed view

Demand, supply, and finance

Monthly SIOP review

Review period

Oct

Product families

3

Open exceptions

2

Product family	Constraint	Review status
Assemblies	Material receipt unconfirmed	Supply review
Components	Shared line capacity	Operations review
Service parts	Inputs confirmed	Ready for decision

Each exception retains its source, reporting period, and responsible owner.

Real estate: Match leases, collections, and operating costs to properties and entities for the same period. Keep scheduled rent, cash receipts, and receivables separate. Our property management reporting article describes those inputs. Check the approved way to access the property system before the provider promises a connection.

Test access, stale data, and support before launch

Ask every provider to run these checks on the report or app you will use. Use separate user accounts and real query or export requests, so the test covers the backend as well as the screen.

• Request another company’s records as a user who lacks access. Confirm the query and export paths deny the request.
• Revoke a user or app grant, then repeat the request from an existing session. Confirm the change takes effect.
• Stop a source refresh. Check that the report shows its last successful update and that someone is assigned to fix it.
• Change a reporting rule. Trace the affected numbers back to source records and confirm who approves the change.

Put support responsibilities in the agreement: who repairs connections, checks changed source fields, and updates reports. Apps can reuse the same records and calculations, with approved access and an owner for each new use.

Agree on what the implementation includes

Permute is built for daily or hourly reporting and analysis. Your team approves accounting treatments and forecast assumptions; we prepare the inputs and apply agreed rules. Forecasting engines, close approval, and statutory consolidation with intercompany eliminations remain separate work. A reporting connection reads source records; ERP write-back needs a separately confirmed, permissioned design.

For custom apps, agree on the interface, approved data, and actions before development starts. Permute-hosted apps check current user permissions and app grants on data requests. Builds and source editing happen outside the hosting service, so include any server requirements in the implementation plan.

If the Palantir proposal exceeded your budget, start with the report or app that would make the investment useful. Compare alternatives on the cost to deliver that work and keep it running. A managed implementation includes delivery and support; a development platform needs engineers or a consulting firm to supply them. Price the same sources and requirements, then expand from the first working release.

Questions about Palantir alternatives