Best AI Tools for Data Science in 2026: Pick by Where Your Code Runs
As of 11 November 2026, one data scientist pays $10 to $20 a month for an AI agent in an editor or terminal, and $36 to $39 per editor for a shared AI notebook. Databricks has no flat price: it bills per second, and its free trial still charges your own cloud account for compute.
The short version
Pick by where your code runs. Deepnote (Team $39 per editor) and Hex (Professional $36) are shared notebooks, Runcell is an agent in your own JupyterLab from free to $20 a month, Claude Code and GitHub Copilot work in an editor, and Databricks suits data already on a lakehouse.
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In this guide10 sections
The best AI tool for data science depends on where your code runs: Deepnote or Hex for shared notebooks, Runcell in JupyterLab, Claude Code or Copilot in an editor, Databricks on a lakehouse.
That is what decides the buy. A tool that edits notebook cells is no help when your analysis lives in a folder of Python scripts, and a lakehouse is wasted on a dataset that fits on a laptop. Every price below was read on the vendor's own pricing page, dated.
Hokai card of the six picks and where each one works. Source: the vendors' pricing pages, read 11 November 2026.
The shortlist: one tool per place your code runs
| Tool | Where it works | Entry price | Fits |
|---|---|---|---|
| Deepnote | Cloud notebook with an agent | Free, Team $39 per editor | Teams sharing notebooks |
| Hex | Notebooks that publish as apps | Free, Professional $36 per editor | Analysts who share results |
| Runcell | Agent inside your JupyterLab | Free, Pro $20/month | Solo work in Jupyter |
| Claude Code | Agent in a terminal or VS Code | Pro $20/month | Script and report projects |
| GitHub Copilot | Assistant in your editor | Free, Pro $10/month | The cheapest start |
| Databricks | Lakehouse for data and ML | Pay per second | Teams on a lakehouse |
Deepnote's Team price is billed yearly. Four of these pricing pages were read on 11 November 2026, Claude's on 2 November and GitHub's on 6 November.
How to choose: where does your code run?
Answer one question first. Is the work a notebook several people share, a notebook only you open, a folder of scripts, or pipelines on a platform?
| If your work is | Pick |
|---|---|
| Notebooks a team edits together | Deepnote |
| Results for people who never open a notebook | Hex |
| Your own JupyterLab, no new workspace | Runcell |
| A project folder of scripts and data files | Claude Code |
| Help in your editor, paying nothing at first | GitHub Copilot |
| Governed pipelines on a lakehouse | Databricks |
If your situation does not fit one row, answer a few questions and get a shortlist matched to your work.
What one data scientist pays a month
Read from each vendor's pricing page. Deepnote is billed yearly.
The editor and terminal tools cost a solo user $10 to $20 a month. The shared notebooks cost about twice that, because they bill per editor and bundle compute.
For a team of three, Hex Professional comes to $108 a month and Deepnote Team to $117. Deepnote's Team plan also bundles monthly AI credits plus CPU and GPU allowances, per its pricing page on 11 November 2026. Databricks has no flat figure to compare: it bills by usage.
Deepnote and Hex: the shared notebooks
Deepnote is a collaborative notebook whose agent plans a task and then adds, edits or removes Python, SQL and text blocks across the whole project, per deepnote.com/pricing on 11 November 2026.
On 11 November 2026 we opened a public Deepnote notebook, a weather forecast built with Prophet, without signing in. It showed a SQL block whose station name is an input parameter, feeding Python that fits the model and plots a 365-day forecast, with Run, Edit and Copy buttons at the top. The Free plan allows 5 agent calls a month, so real use means Team at $39 per editor a month billed yearly, with a 14-day trial.
Hex also starts from the notebook, but its plans count published data apps: Professional allows up to 5 and Team allows unlimited, per hex.tech/pricing on 11 November 2026. Community is free with a trial of its agent. Professional is $36 per editor a month, and students and educators can get it free. Medium compute comes with every paid plan.
Runcell: an agent in the notebook you already have
Runcell runs inside a JupyterLab session you already have open. It writes a cell, runs it, reads the table, chart or stack trace that comes back and fixes its own errors. It also keeps decisions made earlier in the session, such as which columns were dropped, so a later question does not restart the analysis.
Its paid plans offer models from several labs, OpenAI's GPT 5.5 and Anthropic's Claude Opus 4.7 among them. The free Hobby plan gives 20 credits a month and Pro is $20 for 500, per runcell.dev/pricing on 11 November 2026. Heavier plans run up to 10,000 credits.
Claude Code and Codex: agents in the terminal
Claude Code is not a notebook at all, which is the point for anyone whose work lives in scripts. In a test published on 28 July 2026, KDnuggets assistant editor Abid Ali Awan had it write an analysis script, run it on a student burnout dataset, check the results and produce a 146-line Markdown report. It needs Claude Pro, $20 a month, per Claude's pricing page on 2 November 2026.
OpenAI's Codex does the same job and has no subscription of its own. It comes with the ChatGPT plan you already pay for, Free included, per OpenAI's pricing page on 6 November 2026. If your team already pays for ChatGPT, try it before buying a second plan.
GitHub Copilot: the cheapest way in
GitHub Copilot Free gives 2,000 completions a month plus a limited allowance of chat and agent use. Pro at $10 a month makes completions unlimited, per GitHub's plans page on 6 November 2026.
Databricks: for data that already lives on a lakehouse
Databricks bills pay as you go at per-second granularity, with committed-use contracts for larger buyers. Its free trial still bills your own cloud account for compute, per databricks.com/product/pricing on 11 November 2026. Free Edition costs nothing and is meant for students, hobbyists and learners, with smaller compute and fair-use limits, and not for production or commercial use.
A team running governed pipelines across a lakehouse should pick it outright. One or two people exploring a dataset that fits on a laptop should start with a notebook agent and decide later.
If you meant dashboards, not code
ThoughtSpot and Qlik turn a typed question into a governed dashboard, and AI2sql turns it into SQL. None of them writes or runs analysis code, so they are a different buy, compared in the guide to the best AI data analytics tools.
Where a plain chat assistant wins
For a one-off question about one file, you may not need any of these. In the same KDnuggets test, ChatGPT took an uploaded dataset and returned a dashboard-style summary with charts and key metrics, with no code written by hand. A notebook or coding agent earns its cost once the analysis has to be:
- rerun when new data arrives;
- checked by someone other than the person who wrote it;
- shared with people who will not read the code.
If the job is preparing training data rather than analysing it, none of these fits either. Surge AI and Encord produce and manage the labelled data that model training and evaluation need, which is a separate purchase.
Frequently asked questions
How much do AI tools for data science cost?
As of 11 November 2026, the cheapest paid plans for one person are GitHub Copilot Pro at $10 a month, Runcell Pro and Claude Pro at $20, Hex Professional at $36 per editor and Deepnote Team at $39 per editor billed yearly. Databricks bills by usage with no flat price.
Is there a free AI tool for data science?
Yes, several have free plans as of 11 November 2026. Deepnote Free allows 5 agent calls a month, Hex Community is free with an agent trial, Runcell Hobby gives 20 credits a month, GitHub Copilot Free gives 2,000 completions a month, and Databricks Free Edition is free for learning but not for production.
Can Claude Code or Codex do data analysis?
Yes. In a KDnuggets test published 28 July 2026, Claude Code wrote an analysis script, ran it on a dataset and produced a 146-line Markdown report. Claude Code needs Claude Pro at $20 a month; Codex comes with any ChatGPT plan, including Free.
Deepnote or Hex: which should I pick?
Pick Deepnote if the work is several people editing the same notebooks with an agent that edits cells across the project. Pick Hex if results must reach people who never open a notebook, since a Hex project publishes as an app. Hex Professional is $36 per editor; Deepnote Team is $39 billed yearly.
Do I need Databricks for data science?
Only if your data already lives on a lakehouse and you run governed pipelines at scale. Databricks bills per second, and its free trial still charges your own cloud account for compute. For a dataset that fits on a laptop, a notebook agent is the cheaper start.
Covered in this guide
- Claude Code: Anthropic's agent for the terminal, IDEs, desktop, web and mobile that edits files, runs tests and opens pull requests. There is no free plan.
- Databricks: Unified Lakehouse platform for data engineering, analytics, and AI, founded 2013, valued at $190B (Aug 2026), with consumption pricing from $0.08 per DBU on the published Premium tier.
- Runcell: AI agent for Jupyter notebooks that writes, runs, and debugs code from natural-language prompts, with a free tier and a paid Pro plan for daily analytical work.
- AI2sql: AI2sql is an AI SQL generator that converts natural language descriptions into optimized SQL queries for 10+ database types, supporting PostgreSQL, MySQL, BigQuery, Snowflake with 90% accuracy.
- Encord: Data infrastructure for Physical AI and multimodal teams: annotation, curation, alignment and managed data, used by 300+ AI teams, per the vendor.
- GitHub Copilot: GitHub's AI coding assistant with agent mode, Copilot Fusion model routing and MCP support across 6 IDEs, plus a free plan with no credit card required.
- Codex: Clones a GitHub repo into a sandbox, writes and tests code, then opens a pull request; included in every ChatGPT plan, with the newest GPT-6 models from Plus.
- Qlik: Data analytics and integration platform used by 40,000+ organizations worldwide.
- Surge AI: Surge AI powers RLHF for Anthropic, OpenAI, and Google, run by a PhD-heavy expert annotator network. Custom enterprise pricing; no free tier or self-serve signup.
- ThoughtSpot: AI-Powered Agentic Analytics Platform for Self-Service Business Intelligence
Sources
Still deciding?
This guide covers a handful of options. Smart Match checks every listing in the directory against how you actually work and what you can spend, then hands you the shortlist and the reason behind each pick.
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