Is Alteryx AI-native? Not from the ground up, though 2026 brought it a lot of new AI. Alteryx One is a mature visual canvas that added Ask Alteryx, which configures tools and explains workflows, and Agent Studio, which turns governed datasets into conversational agents.
(If your renewal date is the real reason you're reading this, you're in good company.) For a team shopping now, the useful question is who builds the workflow. In Alteryx you build by hand with AI riding along, while AI-native alternatives build from a plain-English goal for you to review.
Short version, if you only have a minute:
If you want an Alteryx alternative that's AI-native from the ground up, Prophecy is the strongest pick, because agents build the workflow from plain English, analysts inspect every step, and it runs in your own Databricks, Snowflake, or BigQuery.
Six more Alteryx competitors made the cut, sorted by who does the building. Databricks brings data prep at big-platform scale, Maia (from Matillion) hands pipeline engineering to agents, and KNIME keeps a free visual canvas.
Dataiku ties prep to machine learning, dbt gives analytics engineers tested, version-controlled transformations, and Hex covers quick, code-first ad hoc analysis for data teams.
Alteryx's AI, in plain terms
Ask Alteryx, formerly called Copilot, adds and configures tools on your canvas, suggests next steps, documents and troubleshoots workflows, and can run them. A newer mode, Ask Alteryx for Live Query, answers plain-English questions against Snowflake, BigQuery, and Databricks.
Agent Studio launched in July 2026 and turns governed datasets into conversational agents, still in Public Preview. The Alteryx MCP Server lets AI apps like ChatGPT, Claude, and Copilot Studio build, run, and schedule Alteryx assets, MCP being a standard way for AI tools to connect to software.
All of it requires the quote-based Professional or Enterprise edition. Starter, which costs $250 per user/month billed annually as of October 2026, gets none of these AI features.
That's AI-assisted work: smart help on a canvas you still build by hand, which suits a team that already lives in Designer. An AI-native tool flips the order, so AI builds the workflow from your goal and a person reviews what it built.
1. Prophecy: AI agents that build data prep you can inspect
Who it's for: business users such as financial analysts, actuaries, and operations analysts who need prepared data without filing an engineering ticket. HSBC and SAP are among the companies on its homepage.
The AI part: you describe the goal in plain English, and the Transform Agent builds a visual workflow that you inspect, refine, and validate before anything reaches production. The agent never deploys on its own (a fine instinct around finance numbers).
Every step lands on the canvas as a gem, the platform's name for a single box that does one job, such as Filter, Join, Pivot, or FuzzyMatch. You can open any gem in a visual or code view, run the pipeline up to that point, and profile the interim data for null percentages and top values.
Workflows compile to SQL, the language your warehouse already runs, and that SQL lives in Git, which tracks every version. On paid plans, they run inside your own Databricks, Snowflake, or BigQuery account under the governance you already have.
The agent can also explore the prepared data in chat and generate Analyses, dashboards of insights and recommendations tied to the pipeline that produced them.
For Alteryx shops, the importer takes Designer files from version 2023.2 onward and gets a workflow roughly 90% of the way, so an analyst only has the remainder to finish, with AI help.
Unmapped tools, such as the spatial FindNearest, arrive as a "todo" gem to finish by hand, and a built-in scheduler runs workflows on a timer or when a file lands in S3 or SFTP.
Price check (October 2026): Starter is free with 20 credits a month, Professional is $150 per user/month, and Enterprise Express is $4,000/month for up to 20 users, billed annually. Enterprise is custom, and paid plans add processing in Databricks, Snowflake, and BigQuery.
The trade-off: the free Starter tier runs on embedded DuckDB, a small database engine built into the app, with 20 credits a month. That's plenty for kicking the tires, though a real evaluation on your warehouse data means a paid plan.
2. Databricks: big-data prep and AI for platform teams
Databricks is the strongest AI-native pick for teams whose data already lives in a lakehouse, which is a data lake and a data warehouse rolled into one platform.
Who it's for: data and platform teams on the Databricks Data + AI Platform, plus the analysts they support. If your company already pays for Databricks, a lot of the plumbing is done.
The AI part: Lakeflow Designer, generally available since June 2026, is a no-code drag-and-drop prep canvas built on Genie Code, Databricks' agentic coding assistant. You describe a transformation in plain English, and Genie Code generates or edits the workflow.
The result is code governed by Unity Catalog, the platform's permissions and lineage layer.
More than 3,000 customers have used Lakeflow Designer, according to Databricks. Business users also get Genie One for chat-style questions and Genie Agents, formerly Genie spaces, which data teams configure with trusted metrics and rules.
For an Alteryx move, know that Databricks never names Alteryx, still lists it as a partner, and describes bulk migration through Lakebridge as upcoming. Plan on rebuilding workflows for now.
Price check (October 2026): pay-as-you-go in DBUs, Databricks' unit of compute, with SQL Serverless listed at $0.70 per DBU on AWS US East. Lakeflow Designer itself carries no per-user fee, and a 14-day trial and a quota-limited Free Edition are both available.
Genie One and Genie Agents are free for users through January 31, 2027, though that covers LLM usage only and compute is still billed.
The trade-off: it's Databricks-only, and the setup sits with your data team, since Genie's answers are only as good as the data, metrics, and rules they configure.
3. Maia: handing pipeline engineering to a team of agents
Maia, Matillion's AI data automation platform, is the pick for data teams that would happily hand pipeline grunt work to agents.
Who it's for: data teams on Snowflake, Databricks, Amazon Redshift, or Google BigQuery, chosen once at project setup. Maia says it's "Trusted by 1,000+ data teams."
The AI part: Maia Team is a set of agents that plan, build, test, deploy, and fix pipelines. Each request becomes a step-by-step plan, and nothing changes until a human approves it.
The work runs as pushdown ELT, meaning data is loaded first and then transformed inside your own cloud data platform. You get a low-code canvas plus SQL and Python, 150+ connectors, and Maia Foundation underneath, which is what Matillion's Data Productivity Cloud is called now.
For Alteryx teams, the Migration Agent lists Alteryx under its supported platforms and promises "Individual pipelines converted in minutes, and full migration projects completed in weeks." That's Maia's claim, and access runs through a sales demo, so bring your gnarliest workflow to the call.
Price check (October 2026): consumption-based credits across Developer, Teams, and Scale editions, with no published dollar prices. A 14-day free trial includes 500 credits.
The trade-off: it's built and sold for data teams, and it needs a cloud data platform. Maia itself says it "requires a mindset shift from manual building to goal-based oversight," and you'll want a quote before anyone gets attached.
4. KNIME: a free, open-source canvas for visual builders
KNIME is the closest thing to an Alteryx-style canvas you can download for free, which makes it the budget-friendly AI-assisted option here.
Who it's for: analysts who like building workflows node by node on a desktop and would like to stop paying for seats. KNIME Analytics Platform is open source under GPLv3, with 300+ connectors and statistics, machine learning, and GenAI on one canvas.
The AI part: the K-AI assistant helps you build, and since version 5.12 in July 2026 its build mode inspects your workflow before changing anything. It can also build data apps from a prompt.
KNIME ships nodes for building your own agents and MCP services, too. K-AI itself runs on OpenAI GPT-4.1 models, and you can't swap in a different provider.
Price check (October 2026): the Analytics Platform costs nothing, and a free account includes 20 K-AI interactions a month. Pro runs from $19/month (500 K-AI interactions), Team from $99/month with three users, and Business Hub pricing is on request.
The trade-off: it's AI-assisted, so you still build the workflow while K-AI helps. Free local batch execution was deprecated in April 2026, so scheduling and automation now mean a paid plan (the word "free" comes with an asterisk these days).
5. Dataiku: data prep that feeds machine learning
Dataiku makes the most sense when the data you prepare is headed straight into a machine learning model.
Who it's for: data science teams and enterprises that want "analytics, models, and AI agents together in a single governed system," in Dataiku's words. Dataiku also says it's been a Leader in the Gartner Magic Quadrant for AI Platforms for Data Science and ML for the "fifth consecutive year."
The AI part: Cobuild, generally available since June 18, 2026, lets you "Describe a goal and Cobuild builds the pipelines, models, agents, and apps as a visual Flow" that you review. That counts as AI-native by any fair definition.
It sits next to a Prepare recipe with "100+ built-in data transformers," visual recipes or Python, R, and SQL, LLM Mesh for governing access to language models, and visual AutoML.
Dataiku's Alteryx converter is available to partners only, so moving off Alteryx is a rebuild that Cobuild and partners speed up.
Price check (October 2026): quote-based, with a 14-day free trial that needs no card and a self-installed Free Edition.
The trade-off: that's a lot of platform, with an enterprise price tag to match, if all you need is prep and analysis. If nobody on your team builds models, you'd be paying for a whole kitchen to make toast.
6. dbt: tested SQL transformations for analytics engineers
dbt fits teams that want every transformation written as version-controlled, tested SQL that runs in the warehouse.
Who it's for: analytics engineers, the SQL-fluent people who sit between data engineering and the business. Fivetran and dbt Labs finished merging in June 2026, and the hosted product is now called the dbt platform.
The AI part: dbt Wizard, the recommended AI agent for governed data development, is in Public Preview. dbt Copilot handles natural-language requests inside Canvas, a drag-and-drop editor whose models compile to SQL.
dbt v2, built on a Rust engine, is generally available, and dbt Core lives on as dbt v1 under the Apache 2.0 open-source license. Next to Alteryx, it covers transformation logic well and leaves spreadsheet-style self-service to other tools.
Price check (October 2026): the Developer plan is free for one seat, Starter is $100 per developer seat/month, Enterprise and Enterprise+ are custom, and the open-source engine is free.
The trade-off: you need SQL and a warehouse, because dbt runs SQL against your data platform and has no compute of its own. Canvas is limited to Enterprise and Enterprise+, so business users on lower tiers get no visual editor.
7. Hex: notebooks for fast, ad hoc analysis
Hex is built for one-off questions that need an answer and a chart before the meeting starts, worked out in notebooks, which are documents that mix code, results, and charts on one page.
Who it's for: SQL and Python analysts and data teams who already think in queries. Hex Community is free, so trying it costs nothing but an afternoon.
The AI part: the Notebook Agent writes and edits SQL, Python, and chart cells, and Hex aims it at technical users who can audit the code it suggests. Threads gives non-technical colleagues a plain-language way to ask their own questions, which takes some pressure off the data team.
Next to Alteryx, Hex covers the analysis end of the job and leaves visual prep to other tools.
Price check (October 2026): Professional is $36 per editor/month, Team is $75 per editor/month, and Enterprise is custom. AI runs on credits, 30 per editor each month on Professional and 40 on Team, with top-ups at $25 per 50 credits.
The trade-off: it's code-first with no no-code prep canvas, and the AI is metered, so heavy agent users will keep one eye on the credit counter.
Choosing by how much work you want AI to do
The cleanest way to shortlist is to decide how much of the building you want to hand over, then match the tool to that answer.
AI builds, you review: the #1 pick, Maia, Dataiku's Cobuild, and Databricks' Lakeflow Designer all start from a plain-English goal. The #1 pick is aimed at business analysts, Maia at data engineers, Dataiku at data science teams, and Lakeflow Designer at analysts inside a Databricks shop.
AI helps, you build: KNIME's K-AI, dbt Copilot, and Hex's Notebook Agent speed up hands-on work on a canvas, in SQL, or in a notebook. They suit people who enjoy building and want fewer clicks.
AI answers questions: Genie One, Hex Threads, and Ask Alteryx for Live Query are for asking, and they work best once someone has prepared the data.
Whatever you pick, what I'd test first is one real Alteryx workflow your team relies on every week, rebuilt or imported during the trial, with a second person checking each step.
Is Alteryx AI-native enough? When staying put is the right call
Sometimes the best Alteryx alternative is the Alteryx you already have, with its new AI switched on. Three situations make a strong case for staying.
Spatial work: if your workflows lean on spatial tools, check every importer carefully, because the #1 pick's importer leaves spatial tools such as FindNearest for you to rebuild by hand.
Macro-heavy desktop workflows: years of nested macros in Designer Desktop are expensive to move, and a migration that stalls halfway can cost more than the license you were trying to cut.
A team that's happy on Designer with Ask Alteryx: if your analysts are productive, your edition already includes the AI, and nothing is breaking, a migration mostly buys you disruption.
Even Dataiku says the switching costs might not pay off for a team already proficient in Alteryx that mainly needs repeatable automation for Excel-based work.
Everyone else should run a trial, and I'd start with the workflow your team complains about most.
FAQ
Does Alteryx have an AI agent?
Yes, Agent Studio, launched in July 2026, lets business users turn governed datasets into conversational agents on Alteryx One Professional and Enterprise. Those agents are in Public Preview, and Alteryx says their answers come from its own analytics engine.
What happens to Alteryx schedules when you migrate?
Schedules stay behind, so you set them up again in the new tool after the workflow logic moves. Prophecy's importer gets a workflow roughly 90% of the way and you rebuild schedules in its built-in scheduler, while Maia's Migration Agent also lists Alteryx as a supported platform.
Is dbt an Alteryx alternative for business analysts?
It works for analysts who are comfortable writing SQL, because dbt is built around version-controlled SQL that runs in your warehouse. Its visual Canvas editor, which compiles drag-and-drop models to SQL, is limited to Enterprise and Enterprise+ plans.