--- title: "Cursor vs Claude Code for Data Teams: A 2026 Comparison" url: "https://atlan.com/know/ai-agent/ai-agent-harness/cursor-vs-claude-code-for-data-teams/" description: "Cursor vs Claude Code for data teams: compare models, prompt handling, notebooks, and 2026 pricing, plus how both get enterprise context through MCP." author: "Kovid Rathee" author_role: "Head of Solution Architecture, Data & AI, Nexifi" published: "2026-10-16" updated: "2026-10-16" --- ## What is the difference between Cursor and Claude Code for data teams? Cursor is an editor-first coding agent with Tab completion, a model picker across providers, and its own Composer model. Claude Code is a terminal-first agent, also available in VS Code and JetBrains, that runs Claude models on Anthropic, Amazon Bedrock, Google Cloud, or Microsoft Foundry. Cursor says every request goes through its servers for final prompt building, even with your own API keys. Both support MCP, skills, hooks, subagents, and AGENTS.md. Neither carries metric definitions, lineage, or access rules unless a context layer serves them over MCP. The comparison covers four areas: - **Models and prompts**: which models each tool runs and where the prompt is built - **Data work**: notebooks, large changes, and self-hosted execution - **Cost**: individual, team, and enterprise pricing as published in October 2026 - **Context**: how both tools reach enterprise knowledge through MCP ## Key takeaways - Cursor routes every request through its servers for final prompt building, even when you bring your own API keys. - Cursor offers many model providers plus its own Composer model. Claude Code runs Claude models on four platforms. - Claude Code reads notebook outputs and can run cells through its VS Code extension. Cursor edits notebook cells. - Neither sees metric definitions or lineage until a context layer serves them. Atlan MCP connects to both. --- Cursor and Claude Code can both write SQL, dbt models, and Airflow DAGs. They differ in where the prompt is built, which models they run, and how much of the work happens in an editor versus a terminal. Those differences matter for a data team that has to answer where its data goes. Neither tool knows what "active customer" means in your warehouse, which is where a [context layer](https://atlan.com/know/what-is-context-layer/) comes in. This page compares the two on data work specifically. For the wider field, including Devin Desktop, see the [three-way comparison of Cursor, Windsurf, and Claude Code](https://atlan.com/know/ai-agent/ai-agent-harness/cursor-vs-windsurf-vs-claude-code-data-context/), and for the enterprise controls side, see [Claude Code and Codex in the enterprise](https://atlan.com/know/ai-agent/context-layer/claude-code-codex-context-gap/). ### Shortlist an Agent Harness for Your Team Takes what you are building, who maintains it, deployment model, and governance needs, and returns a ranked shortlist of up to three harnesses with the deciding trade-off for each and what breaks first. [Read the skill](/skills/agent-harness-picker.md). *Paste into a new chat* ``` Use the skill at https://atlan.com/skills/agent-harness-picker.md to pick an agent harness for our team. Ask me for whatever it needs. ``` *Run once in a terminal* ``` curl -fsSL --create-dirs \ -o ~/.agents/skills/agent-harness-picker/SKILL.md \ https://atlan.com/skills/agent-harness-picker.md ``` *For an agent* ``` curl -fsSL https://atlan.com/skills/agent-harness-picker.md ``` Human Agent ClaudeChatGPTGeminiCursorOther Copy | | | |---|---| | **Interface** | Cursor is an editor with an agent panel and [Tab completion](https://cursor.com/help/ai-features/tab). Claude Code starts in the terminal and also runs in [VS Code](https://code.claude.com/docs/en/vs-code) and [JetBrains](https://code.claude.com/docs/en/jetbrains) | | **Models** | Cursor runs models from [several providers plus its own Composer](https://cursor.com/docs/models-and-pricing). Claude Code runs Claude models, and [Anthropic does not support routing it to non-Claude models](https://code.claude.com/docs/en/llm-gateway) | | **Prompt path** | Cursor says [all requests are routed through its servers for final prompt building](https://cursor.com/help/models-and-usage/api-keys), including with your own keys | | **Notebooks** | Both work with Jupyter. Cursor edits cells in the editor; Claude Code edits by `cell_id` and reads outputs | | **Entry price** | Cursor Free at $0, paid from [$8 a month](https://cursor.com/docs/models-and-pricing). Claude Code starts on [Pro at $20 a month](https://claude.com/pricing) | | **Enterprise context** | Neither has it by default. Both reach it through MCP servers, in [Cursor](https://cursor.com/docs/mcp) and in [Claude Code](https://code.claude.com/docs/en/mcp) | --- ## What are the key similarities between Cursor and Claude Code? The two tools share more architecture than their interfaces suggest. The same [agent loop](https://atlan.com/know/ai-agent/what-is-an-agent-loop/) sits underneath both: the model plans, calls a tool, reads the result, and repeats until the task is done. Both are [agent harnesses](https://atlan.com/know/what-is-an-agent-harness/), the subject of [harness engineering](https://atlan.com/know/what-is-harness-engineering/). The overlap shows up in the extension points: - **Instruction files.** Cursor reads [`AGENTS.md`](https://cursor.com/docs/rules) as an alternative to its own rules files. Claude Code [reads `AGENTS.md` too](https://code.claude.com/docs/en/memory) when a repository has no `CLAUDE.md`. A single well-written file, as described in [how to write AGENTS.md](https://atlan.com/know/how-to-write-agents-md/), serves both. - **Skills.** Both support [agent skills](https://atlan.com/know/ai-agent/ai-agent-skills/what-are-agent-skills/): Cursor documents them as [an open standard for extending agents](https://cursor.com/docs/skills), and Claude Code has [its own skills documentation](https://code.claude.com/docs/en/skills). The tradeoffs against tool servers are covered in [agent skills vs MCP](https://atlan.com/know/ai-agent/ai-agent-skills/agent-skills-vs-mcp/). - **MCP.** Cursor [connects to external tools and data sources through MCP](https://cursor.com/docs/mcp), and Claude Code [connects to hundreds of them](https://code.claude.com/docs/en/mcp). Background on the protocol is in [what is MCP](https://atlan.com/know/what-is-model-context-protocol/) and the [MCP architecture deep dive](https://atlan.com/know/ai-agent/mcp-architecture-deep-dive/). - **Hooks and plugins.** Cursor documents [hooks](https://cursor.com/docs/hooks) and [plugins](https://cursor.com/docs/plugins) that bundle rules, skills, MCP servers, and hooks. Claude Code has [hooks](https://code.claude.com/docs/en/hooks) and [plugins](https://code.claude.com/docs/en/plugins) too. - **Subagents.** Cursor lets its agent [delegate to subagents](https://cursor.com/docs/subagents), each in its own context window. Claude Code has [subagents](https://code.claude.com/docs/en/sub-agents) as well. - **Sandboxing.** On macOS, Cursor's sandbox runs commands under [Seatbelt](https://cursor.com/docs/agent/security/run-modes), and so does Claude Code's [sandboxed bash tool](https://code.claude.com/docs/en/sandboxing). Code search is where they diverge. Cursor's [Instant Grep](https://cursor.com/docs/agent/tools/search) builds and queries its index on your machine and does not upload file paths or code to build it, though a file the agent opens can still end up in a model request. --- ## How do Cursor and Claude Code differ for data work? A data team's week spans warehouse modeling on a platform like Snowflake or Databricks, often with dbt; pipelines in an orchestrator such as Airflow; grants and masking policies; and ad-hoc analysis in SQL, notebooks, and BI tools. Both tools can touch all of it. They handle it differently. ### Cursor vs Claude Code: side-by-side comparison | Feature | Cursor | Claude Code | |---|---|---| | Interface | An editor where you see diffs and accept or reject them in place. It installs third-party extensions from [Open VSX](https://cursor.com/help/customization/extensions), and many popular VS Code extensions are available there. | Terminal-first, with [VS Code and JetBrains](https://code.claude.com/docs/en/vs-code) extensions that show proposed edits in the IDE's own diff viewer, one change at a time. | | Inline completion | [Tab](https://cursor.com/help/ai-features/tab) predicts multi-line edits and cross-file changes, then jumps to your next edit. That helps when one change ripples through downstream models and pipeline files. | Works from prompts and reviewable edits. Its documentation describes [accepting or rejecting proposed changes](https://code.claude.com/docs/en/vs-code), not completions as you type. | | Models | OpenAI, Anthropic, Google, and others, plus Cursor's own [Composer 2.5](https://cursor.com/docs/models/cursor-composer-2-5). On Teams and Enterprise, [Cursor Router](https://cursor.com/docs/cursor-router) can pick a model per request when you choose Auto. | Claude models, through Anthropic or [Amazon Bedrock](https://code.claude.com/docs/en/amazon-bedrock), [Google Cloud's Agent Platform](https://code.claude.com/docs/en/google-vertex-ai), or [Microsoft Foundry](https://code.claude.com/docs/en/microsoft-foundry). | | Prompt path | All requests are [routed through Cursor's servers for final prompt building](https://cursor.com/help/models-and-usage/api-keys), including when you use your own API keys. | On a cloud platform, Claude Code [signs in with your own cloud credentials](https://code.claude.com/docs/en/amazon-bedrock) and calls that platform's model endpoint. | | Self-hosted execution | [Self-Hosted Machines](https://cursor.com/docs/cloud-agent/self-hosted/choose-runtime) run Cloud Agent tool calls on hardware you control, while the agent loop still runs in Cursor's cloud. | [Self-hosted environments](https://code.claude.com/docs/en/self-hosted-environments) run cloud sessions on your own runners, in public beta on Team and Enterprise. Terminal and IDE sessions already run on the developer's machine. | | Large and parallel changes | [Cloud Agents](https://cursor.com/docs/cloud-agent) work in multi-repo environments and open pull requests in each repo they change. | [Dynamic workflows](https://code.claude.com/docs/en/workflows) run many subagents from a script, suited to codebase-wide migrations and sweeps. | | Notebooks | The agent can [create and edit cells in Jupyter notebooks](https://cursor.com/changelog/1-0). | [`NotebookEdit`](https://code.claude.com/docs/en/tools-reference) edits cells by `cell_id`, the Read tool returns every cell with its outputs, and the [VS Code extension](https://code.claude.com/docs/en/vs-code) can ask the editor to run cells. | Large migrations show the difference most. Onboarding a source or moving a warehouse touches dozens of models, tests, and dashboards, and both tools now have a managed way to fan that work out. On notebooks, Claude Code's Read tool returns code, markdown, and visualizations together, and its VS Code extension asks you to confirm before it runs anything in the kernel. --- ## Where does your prompt go, and who retains it? With Cursor, [requests are routed through Cursor's servers for final prompt building](https://cursor.com/help/models-and-usage/api-keys). Cursor's [data use page](https://cursor.com/data-use) says the same about bring-your-own-key setups. It also says that with Privacy Mode on, Cursor holds zero data retention agreements with its model providers. The gap is in the key itself: Cursor states that its [zero data retention policy does not apply when you use your own API keys](https://cursor.com/help/models-and-usage/api-keys), so handling follows your provider's policy. A team that brings its own key for control gets less of it than expected. With Claude Code, the path depends on where you run it. Through Amazon Bedrock, Google Cloud's Agent Platform, or Microsoft Foundry, Claude Code [authenticates with your cloud credentials](https://code.claude.com/docs/en/third-party-integrations), and Anthropic's documentation points to those platforms' own [data retention policies](https://code.claude.com/docs/en/zero-data-retention) for that route. Through Anthropic directly, [zero data retention](https://code.claude.com/docs/en/zero-data-retention) is available to qualified accounts on Claude for Enterprise. It needs separate enablement by Anthropic and is not part of the standard plan. The [data usage page](https://code.claude.com/docs/en/data-usage) lists the default retention periods for accounts without it. Neither answer wins in the abstract. A regulated team should read both pages against its own policy. Related reading: [data privacy for AI agents](https://atlan.com/know/data-privacy-for-ai-agents/) and [AI agent governance](https://atlan.com/know/ai-agent-governance/). --- ## What do Cursor and Claude Code cost for a data team? Cursor replaced its price list recently, so older comparisons are out of date. The figures below come from the vendors' pricing pages as of October 16, 2026. | Tier | Cursor | Claude Code | |---|---|---| | Free | [Free at $0](https://cursor.com/docs/models-and-pricing), limited usage | [Not included](https://claude.com/pricing) on the Free plan | | Individual | [Plus $8, Premium $30, Super $100, Ultra $200](https://cursor.com/pricing) per month | [Pro $20 a month](https://claude.com/pricing) ($17 on annual billing); Max from $100 a month | | Team | [Teams seats at $30, $100, or $200](https://cursor.com/docs/account/teams/pricing) per user per month | [Standard seat $20, Premium seat $100](https://claude.com/pricing) per month on annual billing, or $25 and $125 monthly | | Enterprise | Custom pricing | [$20 per seat per month, billed annually](https://claude.com/pricing), 20-seat minimum, with usage cost on top | Two details change the math. On Cursor, the [Plus plan runs Cursor's own models only](https://cursor.com/docs/models-and-pricing): third-party models arrive at Premium and above, billed at API list price from prepaid credit, and your own API keys are not part of Plus. And Cursor says plans created before its new price list, such as Pro, Pro+, and Teams Standard seats, [keep working as they are](https://cursor.com/docs/account/teams/pricing). So a team's real cost depends on when it signed up. On the Claude side, cloud platform routes bill pay-as-you-go through [AWS, Google Cloud, or Azure](https://code.claude.com/docs/en/third-party-integrations) instead of a seat. --- ## How do Cursor and Claude Code get organizational knowledge and context? Both tools read the checked-out repository and the instruction files inside it. Beyond that, each relies on MCP to reach anything outside the repo. For data work, the missing pieces are rarely in the repository. The meaning of a metric, the [lineage](https://atlan.com/know/ai-agent/data-for-ai/data-lineage-for-ai/) of a table, and the privacy rules on a column live in the systems where they were defined. That is [tribal knowledge](https://atlan.com/know/data-for-ai/tribal-knowledge/) spread across [systems of record, data, and knowledge](https://atlan.com/know/ai-agent/data-for-ai/systems-of-record-data-knowledge/). An agent that cannot see it still writes SQL that runs. It just writes SQL against the wrong table, the failure mode examined in [text-to-SQL for the enterprise](https://atlan.com/know/ai-agent/data-for-ai/text-to-sql-for-enterprise/). See also the [common context problems data teams hit](https://atlan.com/know/common-context-problems-data-teams-building-agents/). MCP lets either tool connect straight to a warehouse or an orchestrator. There are servers for [dbt](https://atlan.com/know/mcp/mcp-server-for-dbt/), [Snowflake](https://atlan.com/know/mcp/mcp-server-for-snowflake/), and [Databricks](https://atlan.com/know/mcp/mcp-server-for-databricks/), and a walkthrough of [connecting a coding agent to a data warehouse over MCP](https://atlan.com/know/ai-agent/how-to-connect-ai-coding-agent-to-data-warehouse-mcp/). The cost shows up when you wire five of them: the model then has to reconcile what five systems say about the same thing, with no shared definition to settle the disagreement. That is the argument for [business context for AI](https://atlan.com/know/business-context-for-ai/) arriving as one governed layer, and it is why [MCP gateways](https://atlan.com/know/ai-agent/mcp-gateway-vs-context-layer/) and context layers solve different problems. --- ## How can Cursor and Claude Code get enterprise context from Atlan? Atlan is the [Context Layer for AI](https://atlan.com/know/what-is-the-enterprise-context-layer/). It connects to the databases, warehouses, transformation tools, orchestrators, and BI tools a data team already runs, and serves what it learns through the [Atlan MCP server](https://atlan.com/know/what-is-atlan-mcp/). According to the [Atlan documentation](https://docs.atlan.com/product/capabilities/atlan-ai/how-tos/remote-mcp-overview), that server lets an agent search enterprise context, traverse end-to-end lineage, read governed definitions and glossaries, and run SQL, with every answer governed by the permissions already set in Atlan. Both tools are on the documented client list, against the same hosted server at `https://mcp.atlan.com/mcp`. Cursor can install it from its plugin marketplace or through a manual MCP entry. For Claude Code, the docs give a one-line `claude mcp add` command and an OAuth sign-in. OAuth runs tools with each person's own permissions and attributes their actions to them. An API key acts as one shared identity, which the documentation recommends for automation and service accounts. Behind that connection sit an [Enterprise Data Graph](https://atlan.com/know/enterprise-data-graph/) of assets and their relationships, an [Active Ontology](https://atlan.com/know/what-is-active-ontology/) of terms, domains, and metric definitions, and [Context Repos](https://atlan.com/know/ai-agent/context-repository-for-ai-agents/) that package context for one use case. The same context then serves whichever tool a developer opens, which is the point of a [model-agnostic context layer](https://atlan.com/know/ai-agent/context-layer/model-agnostic-context-layer/). See also [semantic layers for AI agents](https://atlan.com/know/ai-agent/semantic-layer-for-ai-agents/) and [context engineering for AI agents](https://atlan.com/know/context-engineering-for-ai-agents/). Atlan's walkthrough, Watch a Contact Center Agent Bootstrap Itself: Cursor + Atlan MCP, shows Cursor working against the Atlan MCP server. --- ## Which should a data team pick, Cursor or Claude Code? Pick on the work and the constraint, in that order. Cursor fits teams that live in an editor all day, want Tab to carry a change across files, or want several model vendors behind one tool. Claude Code fits teams that hand over larger, well-specified tasks and review afterward, teams that must keep model traffic on a specific cloud, and teams already standardized on Claude. Because the [VS Code extension installs into Cursor](https://code.claude.com/docs/en/vs-code), the choice is not exclusive, and plenty of teams run both. Whatever you pick, plan the context separately, because neither tool ships with your metric definitions. For the wider harness decision, see [how to build an AI agent harness](https://atlan.com/know/how-to-build-ai-agent-harness/), the [harness tools compared for 2026](https://atlan.com/know/best-ai-agent-harness-tools-2026/), and the [agent context layer tools compared](https://atlan.com/know/ai-agent/agent-context-layer-tools-compared/). For what breaks once agents reach production data, read [data quality for agent harnesses](https://atlan.com/know/data-quality-ai-agent-harnesses/) and [how to structure context for AI agents](https://atlan.com/know/ai-agent/how-to-structure-context-for-ai-agents/). If both tools reach your warehouse through MCP, who owns the definitions they read, and how would you know when two agents answered the same question differently? --- ## FAQs about Cursor vs Claude Code for data teams ### 1. What is the core difference between Cursor and Claude Code for data work? Cursor is an editor with an agent, Tab completion, and a model picker. Claude Code is a terminal-first agent, also in VS Code and JetBrains, built around Claude models. Cursor suits interactive editing of SQL, dbt models, and notebooks. Claude Code suits repository-wide changes you describe once and review afterward. ### 2. Does Cursor send my prompts to its servers when I use my own API key? Yes. Cursor's documentation says your key is sent to its backend with every request because all requests are routed through Cursor's servers for final prompt building. Cursor also states that its zero data retention policy does not apply when you use your own API keys, so data handling follows your model provider's policy. ### 3. Can data teams choose their own models with both tools? Cursor supports models from OpenAI, Anthropic, Google, and others, plus its own Composer model, with your own keys on plans that include them. Claude Code runs Claude models through Anthropic, Amazon Bedrock, Google Cloud's Agent Platform, or Microsoft Foundry. Anthropic does not support routing it to non-Claude models through a gateway. ### 4. Which tool handles Jupyter notebooks better? Both work with notebooks. Cursor's agent can create and edit cells in the editor. Claude Code edits cells by cell ID, reads every cell with its outputs, and in VS Code can ask the editor to run cells after you confirm each run. ### 5. Can I use Claude Code inside Cursor? Yes. Anthropic's VS Code extension for Claude Code has an install link for Cursor, so Claude Code runs inside Cursor's editor window. Many teams run both. ### 6. How do Cursor and Claude Code get enterprise data context? Both connect to MCP servers. Atlan documents setup for both against one hosted server, which exposes search, lineage, governed definitions, and SQL under each person's Atlan permissions with OAuth. --- ## Sources 1. Using your own API keys, Cursor Docs, 2026. https://cursor.com/help/models-and-usage/api-keys 2. Data use and privacy overview, Cursor, 2026. https://cursor.com/data-use 3. Models & Pricing, Cursor Docs, 2026. https://cursor.com/docs/models-and-pricing 4. Pricing, Cursor, 2026. https://cursor.com/pricing 5. Team pricing, Cursor Docs, 2026. https://cursor.com/docs/account/teams/pricing 6. Composer 2.5, Cursor Docs, 2026. https://cursor.com/docs/models/cursor-composer-2-5 7. Cursor Router, Cursor Docs, 2026. https://cursor.com/docs/cursor-router 8. Plans & pricing, Claude, Anthropic, 2026. https://claude.com/pricing 9. Enterprise deployment overview, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/third-party-integrations 10. Claude Code on Amazon Bedrock, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/amazon-bedrock 11. Claude Code on Google Cloud's Agent Platform, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/google-vertex-ai 12. Claude Code on Microsoft Foundry, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/microsoft-foundry 13. LLM gateway configuration, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/llm-gateway 14. Zero data retention, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/zero-data-retention 15. Data usage, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/data-usage 16. Self-hosted environments, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/self-hosted-environments 17. Choose where Cloud Agents run, Cursor Docs, 2026. https://cursor.com/docs/cloud-agent/self-hosted/choose-runtime 18. Cloud Agents, Cursor Docs, 2026. https://cursor.com/docs/cloud-agent 19. Orchestrate subagents at scale with dynamic workflows, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/workflows 20. Tools reference, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/tools-reference 21. Use Claude Code in VS Code, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/vs-code 22. JetBrains IDEs, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/jetbrains 23. Sandboxing, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/sandboxing 24. Run modes and sandboxing, Cursor Docs, 2026. https://cursor.com/docs/agent/security/run-modes 25. Search and Instant Grep, Cursor Docs, 2026. https://cursor.com/docs/agent/tools/search 26. Tab completion, Cursor Help, 2026. https://cursor.com/help/ai-features/tab 27. Extensions, Cursor Help, 2026. https://cursor.com/help/customization/extensions 28. Subagents, Cursor Docs, 2026. https://cursor.com/docs/subagents 29. Create custom subagents, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/sub-agents 30. Hooks, Cursor Docs, 2026. https://cursor.com/docs/hooks 31. Hooks reference, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/hooks 32. Rules and AGENTS.md, Cursor Docs, 2026. https://cursor.com/docs/rules 33. How Claude remembers your project, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/memory 34. Agent Skills, Cursor Docs, 2026. https://cursor.com/docs/skills 35. Extend Claude with skills, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/skills 36. Plugins, Cursor Docs, 2026. https://cursor.com/docs/plugins 37. Plugins overview, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/plugins 38. Model Context Protocol (MCP), Cursor Docs, 2026. https://cursor.com/docs/mcp 39. Connect Claude Code to tools via MCP, Claude Code Documentation, Anthropic, 2026. https://code.claude.com/docs/en/mcp 40. Changelog 1.0, Cursor, 2026. https://cursor.com/changelog/1-0 41. Set up Atlan MCP, Atlan Documentation, 2026. https://docs.atlan.com/product/capabilities/atlan-ai/how-tos/remote-mcp-overview 42. Watch a Contact Center Agent Bootstrap Itself: Cursor + Atlan MCP, atlanHQ, YouTube, 2026. https://www.youtube.com/watch?v=Wv99JChZ3JM ## Next steps - To see Atlan's context layer in action first, watch a recorded demo: [Atlan context layer demos](https://atlan.com/context-layer-demo/) - To see Atlan working on your own data stack, book a demo: [Book a demo with Atlan](https://atlan.com/forms/talk-to-sales-contact/)