The Best Domo Alternatives for Embedded and AI Analytics (2026)
The best Domo alternative depends on why you are leaving. Teams that want governed, consistent metrics on top of their own data warehouse at a published price usually shortlist Holistics or Looker; Microsoft-centric companies default to Power BI; visualization-heavy teams pick Tableau; spreadsheet-native business users gravitate to Sigma; teams that want natural-language search look at ThoughtSpot; and small teams on a tight budget start with Metabase or Zoho Analytics. In 2026 there is a second reason the question comes up so often: Domo agreed in July 2026 to sell substantially all of its business to Progress Software, which puts every Domo renewal on the table.
Domo is a cloud business intelligence platform that bundles data connectors, storage, ETL (Magic ETL), dashboards ("cards"), low-code apps and embedded analytics (Domo Everywhere) into one SaaS product. That all-in-one design is its strength – a business team can go from a Salesforce login to a live dashboard without a data warehouse or a data engineer – and it is also why leaving Domo is harder than leaving most BI tools, because you are replacing four or five layers of a data stack at once.
This guide compares ten Domo alternatives on the things that matter when you migrate off Domo: how business logic is modeled and governed, how self-service works for non-technical users, AI features, embedding, and what you will actually pay. It also covers what Domo's architecture maps to in a modern stack, and a step-by-step migration plan.
Why do teams leave Domo?
Domo works well for the job it was designed for: giving business users fast, polished dashboards on top of hundreds of SaaS sources without asking IT for a warehouse. The friction shows up as the company grows, as the data team matures, and as the analytics budget starts getting scrutinized line by line. The reasons we hear most often fall into five groups.
Domo's own three-minute platform overview, useful context for readers who have not used it (video: Domo).
- Unpredictable consumption costs. Domo moved to a consumption model where you prepay for a pool of credits that are spent on ingesting, transforming, storing and querying data, on workflows and on AI features. User seats are free, which is attractive, but the bill is driven by data activity that is hard to forecast – a new connector that refreshes every 15 minutes or a heavy Magic ETL dataflow can consume credits faster than planned. Domo does not publish list prices; Vendr's marketplace data, as reported by third parties in 2026, puts the median Domo contract at roughly $50,000 per year, with deals ranging from about $11,000 to $175,000. (Our Domo pricing breakdown goes deeper.)
- Business logic that lives in many places. Domo's calculated metrics are written as Beast Mode formulas, which can be saved to a DataSet and shared, and as Magic ETL dataflows. That works at small scale, but there are no code-based, centrally governed semantic layers with version control, code review and tests, so the same KPI tends to get defined slightly differently on different cards, and trust in the numbers erodes.
- Data that is locked inside Domo. Because Domo stores the data it ingests, your transformation logic and history live in a proprietary layer. Teams that have since adopted Snowflake, BigQuery, Databricks or dbt end up running two data platforms and paying for both.
- Limited depth for analysts and engineers. Magic ETL handles common transformations visually, but complex modeling (multi-step joins, nested aggregations, period-over-period logic at scale) tends to need SQL dataflows or workarounds, and dashboard changes cannot be reviewed in Git the way engineering teams review code. Domo's Sandbox feature helps with promoting content between environments, though it is a different workflow from pull requests on a repository.
- Vendor uncertainty. Domo agreed to sell its operating business to Progress Software in July 2026. Progress has historically run acquired products such as Chef, MOVEit and ShareFile for steady maintenance revenue rather than growth, so customers can expect a working product through all of this, but a change of owner is a natural point to re-evaluate.
Replacing Domo means unbundling it
Most "Domo alternatives" lists compare Domo to other BI tools as though you were swapping one dashboard product for another, but they often miss what Domo actually is. Domo is a full data stack in one product, and most of its competitors are only the last layer of that stack, so the first decision is which of Domo's layers you are replacing and what will do each job afterwards.
A governed semantic layer takes over the job of Beast Mode calculations scattered across cards: each metric is defined once and reused by every dashboard and AI question.
| Domo layer | What it does in Domo | Typical replacement in a modern stack |
|---|---|---|
| Connectors (1,000+) | Pull data from SaaS apps and databases on a schedule | Fivetran, Airbyte, Stitch, or the native connectors of your warehouse |
| Storage (Domo's data layer, formerly Vault) | Holds ingested DataSets inside Domo | A cloud warehouse: Snowflake, BigQuery, Redshift, Databricks, or Postgres for smaller volumes |
| Magic ETL / SQL dataflows | Joins, cleans and reshapes data | dbt (or SQL transformations scheduled in the warehouse) |
| Beast Mode calculations | Defines metrics and calculated fields | A semantic layer: Holistics AML, LookML, Omni's model, dbt's metrics, or Cube |
| Cards, pages and Domo Apps | Dashboards and low-code data apps | A BI tool (the alternatives below) |
| Domo Everywhere | Embedded analytics for customers and partners | The BI tool's embedded offering, or a dedicated embedded platform |
| Alerts, scheduled reports, Workflows | Notifications and automation | Built into most BI tools; orchestration in Airflow, Dagster or the warehouse |
Two practical consequences follow from this table. The first is that a team without a warehouse or anyone comfortable with SQL may be better served by another all-in-one product (Zoho Analytics, Power BI with Fabric, or Qlik Cloud with its data integration add-ons) than by a warehouse-native BI tool. The second is that teams that already run a warehouse and dbt are usually paying for two overlapping stacks (their own and Domo's copy of it), and those teams tend to see the largest savings from switching.
What should a Domo alternative offer?
Domo's appeal is that a business user can get from raw data to a shared dashboard without waiting on anyone, so a replacement has to keep that ease of use while fixing what made Domo hard to govern and hard to budget. The criteria below are the ones we used to compare the tools in this guide, roughly in the order Domo customers raise them.
- A semantic modeling layer that grounds AI answers. Metrics, joins and business rules should be defined once and reused everywhere, including by AI. An assistant that writes SQL against raw tables has to guess what "net revenue" means each time, while one that queries a governed semantic layer uses the same reviewed definitions and permissions as every dashboard. In Domo, that logic lives in Beast Mode calculations scattered across cards. Test whether the layer handles the metrics you report on (period-over-period, running totals, percent of total, cohort retention) without workarounds, and whether you can see which metric, filters and joins an AI answer used.
- Self-service exploration for non-technical users. Business users should be able to filter, drill, compare periods and build their own reports from governed datasets, so that a follow-up question does not turn into a ticket for the data team.
- Connectivity and data preparation. Domo bundles more than 1,000 connectors, storage and Magic ETL. Some alternatives bundle these too (Zoho Analytics, Qlik Cloud, Power BI with Fabric), while warehouse-native tools expect you to bring an ingestion tool, a warehouse and a transformation layer such as dbt, and the right choice depends on whether your team already runs that stack.
- AI features and how they are governed. Beyond grounding, the questions are where your data is sent, whether you can bring your own LLM, and whether AI usage is included in the license or billed as credits that grow with adoption.
- Embedded analytics, if you use Domo Everywhere. The evaluation should cover tenant isolation, white-labeling, end-user self-service inside your product, and whether pricing scales with your customer count. (For a broader shortlist, see our best embedded analytics tools guide.)
- Version control and change management. Git-based workflows, pull-request review and separate development and production environments determine how safely metrics and dashboards can change once many people depend on them.
- Pricing you can forecast. Published prices make it possible to model cost before a sales call, and it is worth modeling at two and five times today's usage because consumption-based bills grow with adoption.
- Vendor stability. The pending Progress Software deal makes roadmap commitments, contract assignment terms and data export rights part of the evaluation for any tool, Domo included.
How we evaluated these tools
We scored each tool against Domo on six criteria that come up repeatedly in Domo migrations: how business logic is modeled and governed, self-service exploration for non-technical users, AI features and how they are grounded, embedded analytics, version control and developer workflow, and pricing transparency. Prices come from each vendor's public pricing page where one exists, and from named third-party marketplace data (mostly Vendr) where the vendor only quotes on request. All prices were checked in October 2026 and are list prices before discounts.
What are the best Domo alternatives?
1. Holistics – governed self-service on your own warehouse, at a published price
Holistics is a BI platform built around a code-based semantic modeling layer (AML, with the AQL query language for metrics), analytics-as-code workflows with Git, and drag-and-drop self-service exploration on top of that governed layer. It most directly addresses the problem of Beast Mode calculations duplicated across cards, because every metric is defined once in code, reviewed like software, and reused across every dashboard, every AI answer and every embedded view.
Business users build their own reports in Holistics with natural-language AI or drag-and-drop, on top of the governed model.
How Holistics compares to Domo:
| Capability | Domo | Holistics |
|---|---|---|
| Business logic | Beast Mode formulas + Magic ETL dataflows | AML/AQL semantic layer in code, with reusable metrics and modules |
| Data storage | Stored inside Domo | Queries your warehouse directly; no copy of your data |
| Self-service | Interact with and filter pre-built cards; Analyzer for builders | Drag-and-drop exploration with one-click period-over-period, percent-of-total, cross-filtering and drill-through |
| Version control | Sandbox for promoting content | Native Git (Holistics-hosted or your own repo), branches, pull requests, CI |
| AI | Domo.AI features, credit-metered | Holistics AI answers questions against the semantic layer, respects row-level permissions, supports bring-your-own LLM, and exposes an MCP server for your own agents |
| Embedded | Domo Everywhere, consumption-priced | White-labeled embedded analytics with AI-powered self-service for end users, flat annual pricing by end-user volume |
Pricing: Holistics publishes its prices. The Entry plan is $800/month and Standard is $1,000/month, billed annually, each including the first 10 users, with additional users at $12.50/user/month. A 15-user Standard deployment therefore costs about $12,750 per year. Its embedded analytics is priced separately on flat tiers sized by end-user volume, starting at $3,000/month (billed annually) for up to 5,000 embedded end-users, with no per-viewer fees and no query metering. Tiers run $3,000, $6,000 and $12,000/month for up to 5,000, 15,000 and 50,000 end users, and every tier includes full white-labeling and AI-powered self-service for your customers (a custom report builder with an AI interface, advanced drills and an embedded team workspace); see embedded pricing. A free trial is available.
Best fit: Data teams at roughly 50–1,000-person companies that already have (or are ready to adopt) a warehouse, want one governed definition of each metric, and want business users to self-serve without the numbers drifting. Also a fit for SaaS companies moving off Domo Everywhere that want predictable embedded pricing.
Limitations: Holistics requires a data warehouse or database and does not bundle ingestion or storage, so a Domo migration also means picking a connector tool. Teams used to Domo's visual-only workflow face a learning curve with modeling in code (the data team writes AML; business users never have to). Embedding is iframe-based with signed tokens, which suits most SaaS products but offers less low-level control than a component SDK. Its chart library is broad but less ornate than Tableau's.
2. Power BI – the default for Microsoft-centric companies
Microsoft Power BI is the most widely deployed BI platform, tightly integrated with Excel, Teams, Azure and Microsoft Fabric, with DAX for modeling and Copilot for AI-assisted report building.
A Power BI report built in Power BI Desktop.
| Capability | Domo | Power BI |
|---|---|---|
| Business logic | Beast Mode + Magic ETL | Power Query + DAX measures inside each semantic model |
| Data platform | Bundled | Fabric (OneLake, pipelines, warehouse) or external sources |
| Self-service | Card interaction | Report builder, Q&A, Copilot (requires paid Fabric capacity) |
| Ecosystem | Independent | Microsoft 365, Azure, Excel |
Pricing: Power BI Pro is $14/user/month and Premium Per User is $24/user/month. Fabric capacity starts at about $262.80/month for an F2 SKU (pay-as-you-go), and the larger capacities that let free users view content start at F64, at roughly $5,000/month. Many enterprises already own Pro through Microsoft 365 E5.
Best fit: Companies standardized on Microsoft, where Excel is the analysts' home and the Microsoft licensing is already paid for.
Limitations: DAX has a steep learning curve for complex calculations, and because each semantic model holds its own measures, the same metric can still diverge across models – the same problem many teams are trying to leave Domo to fix. Power BI Desktop, the full authoring tool, runs only on Windows, and multi-developer workflows on PBIX/PBIP files remain clunkier than Git-native tools. Per-user pricing gets expensive when you want to share dashboards with a large viewer audience, which is where Domo's free seats look good by comparison.
3. Tableau – the strongest visual exploration
Tableau is the best-known data visualization platform, owned by Salesforce since 2019, with the deepest chart customization and a large analyst community. Tableau Pulse and Tableau Next add AI-driven metric monitoring and agentic features on Salesforce's data platform.
A Tableau dashboard, where visual exploration depth is the main draw.
| Capability | Domo | Tableau |
|---|---|---|
| Visualization | Broad library, limited fine control | Industry-leading depth and formatting |
| Data prep | Magic ETL | Tableau Prep, live or extract connections |
| Metric governance | Beast Mode | Workbook calculated fields, published data sources, Tableau Semantics on Tableau Next |
| AI | Domo.AI | Tableau Pulse, Tableau Agent |
Pricing: Tableau Cloud Standard lists Creator at $75, Explorer at $42 and Viewer at $15 per user/month, billed annually; Enterprise edition is about $115/$70/$35.
Best fit: Analyst teams whose main reason for leaving Domo is visualization depth or data storytelling, especially in Salesforce-heavy companies.
Limitations: Calculated fields are scoped to workbooks or data sources, so governed, reusable metrics need extra discipline or Tableau's newer semantic features. Viewer seats add up for large audiences, Prep is a separate tool, and there is no native Git workflow for dashboards.
4. Looker – the original code-based semantic layer
Looker is Google Cloud's BI platform, built around LookML, the modeling language that popularized "define a metric once, use it everywhere". Gemini-powered conversational analytics now sits on top of the LookML model.
A Looker dashboard built on LookML models.
| Capability | Domo | Looker |
|---|---|---|
| Business logic | Beast Mode | LookML (centralized, in code) |
| Data storage | Bundled | Queries your warehouse |
| Version control | Sandbox | Native Git |
| AI | Domo.AI | Gemini in Looker, conversational analytics |
Pricing: Looker is quote-only. Third-party data puts Standard edition contracts at roughly $35,000–$60,000 per year to start and the average enterprise contract around $150,000 per year. Gemini usage beyond included allowances is billed per token. See our Looker pricing analysis.
Best fit: Enterprises on Google Cloud with dedicated analytics engineers to own the model.
Limitations: LookML takes specialist skills to maintain, projects grow file-heavy, and more advanced calculations (running totals, percent-of-total, nested aggregations) often require derived tables. Pricing sits at the top of this list, and Looker has no bundled ingestion either.
5. Sigma Computing – spreadsheet-style analysis on the warehouse
Sigma gives business users a spreadsheet-like interface that runs directly against Snowflake, BigQuery, Databricks and other warehouses, with write-back ("input tables") and AI features layered on top.
Sigma's spreadsheet-style workbook running directly on warehouse data.
| Capability | Domo | Sigma |
|---|---|---|
| Interface | Dashboards and cards | Spreadsheet workbook plus dashboards |
| Data storage | Bundled | Live on your warehouse |
| Business logic | Beast Mode | Workbook formulas and shared data models |
| Write-back | Limited (Domo Apps, forms) | Native input tables |
Pricing: Sigma is quote-only. Vendr data cited in 2026 puts the median contract around $62,000 per year, with a range from roughly $17,000 to $133,000.
Best fit: Finance and operations teams that live in Excel and need to work with warehouse-scale data, including planning-style workflows that write data back.
Limitations: Governance depends more on workbook discipline than on a single code-based metric layer, version control is workbook-based rather than Git-native, and you need a cloud warehouse in place before Sigma is useful.
6. Omni – semantic layer plus SQL and spreadsheet flexibility
Omni was founded by former Looker leaders and combines a shared semantic model with a workbook that lets analysts drop into SQL or spreadsheet-style calculations, then promote what they build back into the governed model.
Omni's product demo (video: Omni Analytics).
| Capability | Domo | Omni |
|---|---|---|
| Business logic | Beast Mode | Shared semantic model in code, with workbook-level flexibility |
| Data storage | Bundled | Queries your warehouse |
| Version control | Sandbox | Git integration for the model |
| AI | Domo.AI | AI query assistant grounded in the model |
Pricing: Omni is quote-only. Third-party estimates published in 2026 place typical contracts between $40,000 and $100,000 per year; treat those as directional.
Best fit: Data teams that want Looker-style governance with a faster, more flexible analyst workflow, and that have the budget for a premium tool.
Limitations: Omni is younger than the incumbents, its embedded and enterprise feature set is still filling out, and the lack of public pricing makes early budgeting harder (in our own deal conversations, buyers frequently assume Omni will "land pricey" before they ever see a quote).
7. ThoughtSpot – natural-language search and AI agents
ThoughtSpot is built around search: users type a question in plain language and get a chart back. Its Spotter AI agents (the successor to the older Sage branding) now handle conversational analysis, and Analyst Studio covers SQL and notebook work.
Spotter, ThoughtSpot's AI analyst, answering questions in natural language (video: ThoughtSpot).
| Capability | Domo | ThoughtSpot |
|---|---|---|
| Primary interface | Dashboards and cards | Search bar and Spotter agent conversations, plus Liveboards |
| Business logic | Beast Mode | ThoughtSpot Models (formerly Worksheets) defined in TML |
| Data storage | Bundled | Queries your warehouse |
| Embedded | Domo Everywhere | ThoughtSpot Embedded (Visual Embed SDK) |
Pricing: ThoughtSpot publishes entry tiers. Essentials starts at $25/user/month (5–50 users, up to 25M rows) and Pro at $50/user/month (up to 1,000 users and 250M rows, with 25 Spotter queries per user per month), both billed annually; Pro is also available on usage-based pricing at $0.10 per credit. Enterprise and embedded pricing are quoted, and Vendr data cited in 2026 puts median contracts near $100,000 per year.
Best fit: Organizations with many non-technical users whose main need is fast answers to ad-hoc questions.
Limitations: Search quality depends on careful upfront modeling of the data, chart and formatting control is more limited than in Tableau or Power BI, and costs can climb quickly once usage moves past entry tiers.
8. Qlik Sense – associative analytics with its own data integration
Qlik Sense, now delivered mainly as Qlik Cloud Analytics, is known for its associative engine (every selection highlights related and unrelated values across the whole data model) and for Qlik's data integration portfolio, which makes it one of the few alternatives that can replace both Domo's dashboards and some of its data pipeline work. (For more options, see our Qlik alternatives guide.)
A Qlik Sense app using the associative engine's selections.
| Capability | Domo | Qlik Sense |
|---|---|---|
| Analysis model | Card filters | Associative engine across the whole app |
| Data integration | Bundled connectors + Magic ETL | Qlik data load scripts, Qlik Talend data integration (add-on) |
| AI | Domo.AI | Qlik Answers, Insight Advisor |
Pricing: Qlik Cloud Analytics lists Starter at $300/month, Standard at $825/month and Premium at $2,750/month (capacity-based, billed annually), with Enterprise quoted.
Best fit: Organizations that want an all-in-one replacement closer to Domo's shape, or that already use Qlik's data integration tools.
Limitations: Qlik's load-script modeling is capable but proprietary, the product family is complex to license, and the developer workflow is less Git-friendly than code-first tools.
9. Metabase – open source and quick to deploy
Metabase is an open-source BI tool that connects straight to your database and lets people ask questions through a visual query builder or SQL. It is often the first BI tool a startup installs.
A Metabase dashboard, built with its visual query builder.
| Capability | Domo | Metabase |
|---|---|---|
| Business logic | Beast Mode | Models and metrics in the UI; no code-based semantic layer |
| Data storage | Bundled | Queries your database directly |
| Self-service | Card interaction | Visual query builder + SQL |
| AI | Domo.AI | Metabot (paid add-on) |
Pricing: The open-source edition is free to self-host. Metabase Cloud Starter is $100/month including 5 users plus $6 per additional user, Pro is $575/month including 10 users plus $12 per additional user, and Enterprise starts at about $20,000/year.
Best fit: Startups and small technical teams that need dashboards this week on a small budget.
Limitations: Metric definitions can drift as usage grows (the same issue Domo has), governance and embedding depth sit in the paid tiers, and there is no Git-based workflow for content.
10. Zoho Analytics – the budget all-in-one
Zoho Analytics is a self-service BI tool with built-in connectors, a data preparation layer, the Zia AI assistant and deep integration with the Zoho business suite. Of every tool on this list, it is the closest to Domo's all-in-one shape at a much lower list price.
Zoho Analytics product overview (video: Zoho Analytics).
| Capability | Domo | Zoho Analytics |
|---|---|---|
| Data platform | Bundled | Bundled (connectors, storage, data prep) |
| AI | Domo.AI | Ask Zia, automated insights |
| Deployment | Cloud only | Cloud or on-premise |
Pricing: Zoho offers a free plan for 2 users, and paid plans start at around $24–25/month (billed annually) for small teams, scaling by users and rows.
Best fit: Small and mid-sized businesses, especially Zoho customers, that want Domo's convenience without a warehouse or a data team.
Limitations: Data modeling and governance are basic compared with semantic-layer tools, and large data volumes or complex transformations push against its limits.
Also worth a look: Sisense if your main Domo use case is embedding analytics in a SaaS product, and Lightdash if your team already models everything in dbt.
How do Domo alternatives compare?
| Tool | Business logic | Needs a warehouse? | Version control | AI | Pricing transparency | Starting price |
|---|---|---|---|---|---|---|
| Domo | Beast Mode + Magic ETL | No (bundled) | Sandbox | Domo.AI (credits) | Quote-only | ~$50K/yr median (Vendr) |
| Holistics | AML/AQL semantic layer in code | Yes | Native Git | Semantic-layer-grounded, BYO LLM, MCP | Published | $800/mo |
| Power BI | DAX per semantic model | No | Limited (PBIP, Fabric Git) | Copilot (Fabric capacity) | Published | $14/user/mo |
| Tableau | Workbook calcs, published sources | No | None native | Pulse, Tableau Agent | Published | $15–$75/user/mo |
| Looker | LookML | Yes | Native Git | Gemini in Looker | Quote-only | ~$35K/yr |
| Sigma | Workbook formulas, data models | Yes | Workbook versioning | Sigma AI | Quote-only | ~$62K/yr median (Vendr) |
| Omni | Shared semantic model | Yes | Git | Model-grounded assistant | Quote-only | ~$40K/yr (third-party) |
| ThoughtSpot | Models in TML | Yes | TML + Git | Spotter agents | Partly published | $25/user/mo |
| Qlik Sense | Load scripts, master items | No | Limited | Qlik Answers | Published tiers | $300/mo |
| Metabase | UI models and metrics | No (any database) | None | Metabot (add-on) | Published | Free / $100/mo |
| Zoho Analytics | Data prep + formulas | No (bundled) | None | Ask Zia | Published | Free / ~$25/mo |
How to choose a Domo alternative
The most useful way to choose is to start from the reason you are leaving, since each reason points to a different shortlist.
- If cost predictability is the main problem: Holistics, Power BI, Metabase, Qlik and Zoho all publish prices you can model before a sales call. Holistics' seat-based plans include the first 10 users, and its embedded plans are flat tiers rather than credits.
- If metric consistency is the main problem: Holistics (AML/AQL), Looker (LookML) and Omni define metrics centrally in a governed model. Holistics covers the more complex calculations (running totals, percent-of-total, period comparisons) in the modeling layer at the lowest price point of the three.
- If you have no warehouse and no data engineer: Zoho Analytics or Qlik Cloud keep Domo's all-in-one shape, and Power BI with Fabric is the option if you are on Microsoft.
- If you already run Snowflake, BigQuery or Databricks with dbt: a warehouse-native tool (Holistics, Looker, Omni or Sigma) removes the second copy of your data and the second bill.
- If business users want answers in plain language: ThoughtSpot leads on search, and Holistics AI, Looker's Gemini features and Omni's assistant all answer questions grounded in a governed model, which matters for accuracy.
- If visualization depth drove you away: Tableau remains the strongest choice, with the trade-off that it does nothing to centralize metric definitions.
- If you embed Domo in your product today: compare Holistics' flat embedded tiers, Sisense, and ThoughtSpot Embedded, and model cost at two and five times your current end-user count before you sign.
How to migrate off Domo
A Domo migration is mostly a data-and-logic project with a dashboard project at the end, and teams that sequence it that way finish faster. A six-step plan that works for most mid-sized deployments looks like this:
In Holistics, every model and dashboard change goes through a branch and a review before it reaches production, which makes a phased migration easier to control.
- An inventory of what people actually use. DomoStats and the activity log show which cards, pages and DataSets were viewed in the last 90 days; in most instances a minority of content accounts for nearly all usage, and the rest can be archived rather than rebuilt.
- The warehouse and ingestion come first. Each Domo connector you rely on needs a replacement in Fivetran, Airbyte or your warehouse's native connectors, and historical data has to be exported from Domo and backfilled, which takes longer than teams expect.
- Transformation logic moves into dbt or SQL. Magic ETL and SQL dataflows can be exported and rewritten as version-controlled models, which is also the moment to delete transformations nobody uses.
- Beast Mode logic becomes governed metrics. Each Beast Mode that matters becomes one metric in your semantic layer, defined once, which is where the "different numbers on different cards" problem actually gets fixed.
- The top dashboards get rebuilt and reconciled. The dashboards from step 1 get rebuilt in the new tool and run in parallel with Domo for at least one reporting cycle, with key numbers reconciled side by side so business users trust the switch.
- The cutover is timed to your credit term. Your prepaid credit pool and renewal date set the deadline, so the parallel run should finish before the renewal notice period starts.
Frequently asked questions
Is Domo being acquired?
Domo agreed on July 22, 2026 to sell substantially all of its assets, including its platform, employees and operating business, to Progress Software for $400 million in cash. The deal was pending at the time of writing and was expected to close within Progress's fiscal year ending November 30, 2026, subject to regulatory approvals. The listed Domo company will continue under a new name.
What is the cheapest Domo alternative?
The open-source edition of Metabase is free to self-host, and Zoho Analytics has a free plan for two users, so both cost nothing in license fees for small teams. Among tools with governed semantic layers, Holistics is the lowest-priced published option, at $800/month for its Entry plan including 10 users. The cheapest option overall depends on whether you also need to pay for a warehouse and connectors, which Domo bundled.
Is Power BI a good Domo replacement?
Power BI is a strong replacement for companies already on Microsoft 365 and Azure, since many of them already own Pro licenses and Fabric covers ingestion and storage. It is a weaker fit for companies on Google Cloud or Snowflake-centric stacks, for teams that want Git-based workflows, and for organizations that need to share dashboards with large viewer audiences, where per-user licensing and capacity SKUs add up.
Is Domo similar to Tableau?
Domo and Tableau overlap on dashboards and visualization, but Domo is an all-in-one platform that also stores and transforms your data, while Tableau is primarily an analysis and visualization tool that connects to data stored elsewhere. Teams usually find Tableau stronger for visual exploration and Domo stronger for connecting many SaaS sources quickly. (For a deeper comparison, see our Domo vs. Tableau guide.)
Does Domo have a semantic layer?
Domo lets you define calculated fields as Beast Mode formulas and save them to DataSets so they can be reused across cards, and it offers Magic ETL for transformations. It has no code-based, centrally governed semantic layer with version control and code review comparable to LookML or Holistics AML, which is why metric drift is a common reason teams leave.
Can I keep my data if I leave Domo?
Your DataSets can be exported from Domo, and dataflow definitions can be documented or exported for rebuilding, but the transformation logic and Beast Mode formulas have to be recreated in your new stack. Planning the export early, before the last months of your contract, avoids rushing the most error-prone part of the migration.
Is there a free alternative to Domo?
Metabase (open source, self-hosted), Apache Superset and Lightdash's open-source edition are free to run, and Zoho Analytics and Power BI both have free tiers with limits. Free tools still need someone to host them and a database to query, so the main cost is infrastructure and staff time rather than licenses. If you want to build your own custom BI tool to replace Domo, check out this guide: Replacing $100K Domo stack with open-source this analytics infrastructure
Data Engineer turned Product; writes SQL for a living.