--- title: "Rig vs. the alternatives — compare data platforms" description: "How Rig compares to building it yourself, Claude Code, Workato, Fivetran, Airbyte, Cortex Analyst, Genie, Palantir Foundry, n8n and Glean: a governed data context layer and an action layer, out of the box." canonical: "https://rig.so/compare" format: markdown --- Rig vs. the alternatives # Your data has answers. Most tools can't ask the question BI tools show graphs. Search agents summarise documents. Automation tools move data. Rig deeply understands your complex structured data, and lets you build agents that take action with it. ### Data Agent Platform Build autonomous agents that understand complex internal data. From fraud investigations to churn prevention to revenue ops. ### Auto-Generated Context Our FDE agent builds and maintains rich data context automatically. No endless definitions, schemas stay current as your warehouse evolves. ### Governed Sandbox Every query runs through our orchestrator sandbox. Auditable SQL, permission-aware execution, reduced warehouse bills. ### Question to Action Go beyond dashboards. Data Agents write reports, draft outreach, create CRM deals, and push to 300+ integrated tools. ### Third-Party Agent Ready Connect Claude, ChatGPT, or any AI via Rig MCP. Your context layer and orchestrator serve any agent that needs your data. ### Weeks, Not Quarters Connect your warehouse and start building Data Agents immediately. No six-month implementation or army of consultants. ## Head-to-head How Rig stacks up against tools you might be evaluating. Building it yourselfClaude CodeCortex Analyst (Snowflake)WorkatoGenie (Databricks)Palantir FoundryFivetranAirbyte and StitchQlikViewn8nGlean Rig vs. Building it yourselfA managed platform vs. a DIY data stack Rig Building it yourself Stack RigOne product: ingestion, warehouse, modelling, hosting, AI, and governance Building it yourselfTen products, ten contracts, ten integrations to wire and own Time to value RigConnected and answering in days Building it yourselfSix to nine months to first useful output Headcount RigNo dedicated data team required Building it yourselfA data engineer, then a data team, to build and maintain it Context layer RigSelf-maintaining context that adapts to schema drift Building it yourselfHand-rolled YAML and a Notion doc no one updates, goes stale Governance RigSandboxed queries, RBAC, and a full audit trail from day one Building it yourselfDesign RBAC, sandboxing, and audit logging from scratch [Build and maintain the whole modern data stack yourself, or connect Rig and start today.Read more →](https://rig.so/vs-diy)[What happens when you skip the governance? Read the RBAC horror story→](https://rig.so/rbac-horror-story) Rig vs. Claude CodeA ready-made platform vs. custom-built scripts Rig Claude Code Approach RigConnect your warehouse and go Claude CodeBuild and maintain a bespoke data-query stack Governance RigBuilt-in sandbox, audit trail, and permissions Claude CodeImplement your own guardrails Maintenance RigSemantic layer auto-adapts to schema drift Claude CodeSchema changes mean code changes Agents RigOrchestrator + MCP + \>300 integrations out of the box Claude CodeBuild agent logic from scratch Actionability RigInsights trigger reports, alerts, CRM updates, and workflows automatically Claude CodeYou build the action layer yourself [Claude Code helps you build anything. Rig gives you the data intelligence platform so you don't have to.Read more →](https://rig.so/compare/claude-code)[What happens when you skip the governance? Read the RBAC horror story→](https://rig.so/rbac-horror-story) Rig vs. Cortex Analyst (Snowflake)Multi-source platform vs. single-warehouse assistant Rig Cortex Analyst (Snowflake) Scope RigAny warehouse, database, or API Cortex Analyst (Snowflake)Snowflake data only Context RigAuto-generated and self-updating as your schema evolves Cortex Analyst (Snowflake)You write and maintain YAML semantic files manually Cost control RigSandbox tests every query before execution, blocking invalid or oversized scans Cortex Analyst (Snowflake)Bad, invalid, or runaway scans still burn compute Permissions RigSet once, enforced across every connected AI and SaaS tool Cortex Analyst (Snowflake)Stay inside Snowflake, don't reach Codex, Claude, ChatGPT, Cursor, Slack, or your CRM Actionability RigAgents drive downstream actions: emails, deals, escalations, and more Cortex Analyst (Snowflake)Returns answers, acting on them is manual [Cortex Analyst adds NL queries to Snowflake. Rig turns any warehouse into an autonomous data platform.Read more →](https://rig.so/compare/semantic-layer#cortex-analyst) Rig vs. WorkatoIntelligence layer vs. integration layer Rig Workato Core job RigGetting insight from data and taking action with it WorkatoMoving data between SaaS apps Intelligence RigAI-driven analysis with governed SQL WorkatoRule-based automation Output RigAnswers, reports, and data-driven alerts WorkatoActions triggered across apps Overlap RigMakes sense of what's in those systems WorkatoConnects systems together Actionability RigData-driven agents decide when and how to act, not just shuttle records WorkatoMoves data between apps on a schedule [Workato connects your tools. Rig makes your data talk.Read more →](https://rig.so/compare/workato) Rig vs. Genie (Databricks)Warehouse-agnostic agents vs. warehouse-locked Q&A Rig Genie (Databricks) Scope RigAny warehouse, any source, unified agents Genie (Databricks)Queries inside Databricks only Lock-in RigWarehouse-agnostic, connect anything Genie (Databricks)Databricks-native, requires Unity Catalog Output RigAnswers, reports, alerts, and autonomous actions Genie (Databricks)Answers and visualizations Agents RigFull orchestrator with multi-step reasoning Genie (Databricks)No agent framework Actionability RigAgents trigger workflows, push to CRM, send alerts, and drive decisions Genie (Databricks)Displays answers and charts, no action layer [Genie answers questions inside Databricks. Rig builds agents that work across your entire data stack.Read more →](https://rig.so/compare/semantic-layer#genie) Rig vs. Palantir FoundryMid-market agility vs. enterprise monolith Rig Palantir Foundry Adoption RigHours to days to value Palantir FoundryWeeks to months to value Audience RigMid-market teams, growth-stage companies Palantir FoundryGovernment, defense, large enterprise Pricing RigTransparent, accessible pricing Palantir FoundryCustom enterprise contracts ($$$$) Deployment RigConnect your warehouse, validate accuracy via a risk-free POC, and go Palantir FoundryHeavy implementation + dedicated team Actionability RigOut-of-the-box actions: reports, alerts, CRM updates, 300+ integrations Palantir FoundryActions require custom Ontology apps and engineering [Foundry is built for the Fortune 50. Rig is built for fast-moving startups & mid-market companies.Read more →](https://rig.so/migrate/palantir) Rig vs. FivetranTiered pricing vs. monthly active rows Rig Fivetran Pricing RigMonthly tier with credits included, nothing charged per row FivetranBilled per monthly active row, per connection Scope RigLands the tables, then models them and builds the context layer FivetranLands raw tables and stops dbt Rigdbt Core included, no per-run billing Fivetrandbt Core integration, billed per model run Surprises RigA re-sync costs the same as any other day FivetranA re-sync or backfill shows up on the invoice as active rows Actionability RigGoverned answers, dashboards and actions on the same data FivetranMoves data, answering questions is someone else's job [Fivetran moves your rows and bills you for each one. Rig moves them without a per-row bill and makes them answerable.Read more →](https://rig.so/migrate/fivetran) Rig vs. Airbyte and StitchA whole data stack vs. a connector library Rig Airbyte and Stitch Connectors Rig300+ connectors built on open-source dlt Airbyte and StitchConnector library, self-hosted or cloud Scope RigIngestion, warehouse, dbt and context layer in one product Airbyte and StitchExtract and load, the rest is yours to build Maintenance RigManaged, with schema drift followed through to models and metrics Airbyte and StitchSelf-hosting means you run the upgrades and the on-call Governance RigRole, column and row-level access to the data itself, with an audit trail Airbyte and StitchAccess to the pipeline console Actionability RigGoverned AI access over MCP, dashboards and automations Airbyte and StitchEnds at a loaded table [Airbyte and Stitch hand you tables. Rig hands you answers, on connectors you can still read and fork.Read more →](https://rig.so/migrate/airbyte) Rig vs. QlikViewYour load scripts, rewritten as SQL you own Rig QlikView Status RigActively developed QlikViewMaintained, no end of life; 12.90 support ends 31 Oct 2026 Where data lives RigYour own warehouse QlikViewIn .qvw apps and QVD files Business logic Rigdbt models and certified metrics in SQL, in your git repo QlikViewLoad script and set analysis, run only by Qlik's engine Exploration RigPlain-English questions and dashboards; no associative model QlikViewThe associative model: click a value, everything related filters Deployment RigRig's cloud, or your own cloud account on Enterprise QlikViewYour own Windows servers [Converting to Qlik Sense is the shorter path. Move to a warehouse and Rig if you want your data and logic outside Qlik.Read more →](https://rig.so/migrate/qlikview) Rig vs. n8nAutonomous intelligence vs. rigid workflows Rig n8n User RigAny team member asking questions n8nDevelopers writing workflow logic Approach RigAutonomous reasoning over your data n8nPre-defined triggers and actions Intelligence RigUnderstands what you ask n8nExecutes what you build Flexibility RigSemantic layer adapts to context n8nRigid, breaks when schemas change Actionability RigAgents reason over data and choose the right action autonomously n8nExecutes pre-wired steps, can't decide what to do n8n runs the plumbing. Rig is the brain that decides what to do with the data.Read more → Rig vs. GleanData Agents vs. knowledge search Rig Glean Data type RigStructured: warehouses, databases, metrics GleanUnstructured: docs, wikis, tickets, chat threads AI approach RigData Agents with context layer & orchestrator GleanRAG over documents & knowledge bases Best at RigBuilding agents that query, analyze, and act on data GleanFinding information across your apps Output RigSQL-backed insights, reports, and autonomous actions GleanSummarized answers from documents Actionability RigAgents act on insights: trigger alerts, update CRM, send reports, and more GleanSurfaces information, doesn't drive action Use Glean for knowledge discovery. Use Rig to build Data Agents on your warehouse.Read more → Switching from ## Already on one of these? Start here What moving costs, what you keep, what you lose and who does the work, one page per tool. [Palantir FoundryAn ontology, actions and governed AI without the enterprise programme](https://rig.so/migrate/palantir)[FivetranNothing billed per row, and we build the migration for free](https://rig.so/migrate/fivetran)[Airbyte and StitchOpen-source connectors, plus the warehouse, models and context on top](https://rig.so/migrate/airbyte)[QlikViewQVDs, load scripts and set analysis moved into your own warehouse](https://rig.so/migrate/qlikview)[Warehouse semantic layersCortex Analyst, Genie and the dbt Semantic Layer, compared](https://rig.so/compare/semantic-layer) ## Ready to stop searching and start understanding? See how Rig turns your team's questions into governed, accurate answers, in minutes. [Book a demo](https://rig.so/book-demo) --- - [This page as HTML](https://rig.so/compare) - [Site map for language models](https://rig.so/llms.txt) - [API and agent documentation](https://rig.so/developers)