Product comparison · May 2026
An honest side-by-side comparison of two products that solve overlapping problems differently.
On March 2, 2026, Databricks released its own Excel Add-in into Public Preview. On April 21, Databricks broadened distribution through the Microsoft Office Marketplace and the Microsoft 365 admin center, and added scheduled refresh and AI to the published roadmap. Excel access to cloud data is no longer a niche; it is a permanent enterprise capability that every major data platform will eventually address.
This page compares the Databricks Excel Add-in with Exponam Analyst Intelligence across the dimensions that drive enterprise evaluation: platform coverage, cost structure, data volume, natural-language query, governance, installation, and overall fit. Where the Databricks product is a better choice for a given scenario, this page says so. Where the two products are at parity, this page says so. The goal is a useful evaluation, not a sales pitch.
The single-sentence summary: the Databricks Excel Add-in is a competent first-party tool for Databricks-only workloads in small Databricks-native teams. Exponam Analyst Intelligence is the platform-neutral enterprise layer above the clouds — multi-cloud, AI-powered, privacy-aware, and cost-predictable at any scale.
At a glance
| Dimension | Exponam Analyst Intelligence | Databricks Excel Add-in |
|---|---|---|
| Product maturity | 3+ years in production at Fortune 500 customers (Nasdaq, Eversource Energy, Mizuho, Williams Companies). | Public Preview — released March 2, 2026. |
| Platform coverage | Databricks and Snowflake. Microsoft Fabric and AWS Redshift in active development. | Databricks only. |
| Row capacity | Up to 10,000,000 rows per extract (enterprise license). | Not published. Trial testing returned approximately 948,000 rows from a 2.88M-row dataset before a non-descriptive error. |
| Cost model | Freemium up to 1M rows per query. Enterprise: volume-tiered per-user pricing with a $1,000 / month minimum. | No add-in license fee. Every query consumes Databricks DBUs at the warehouse’s contracted rate. |
| Zero-compute path (Databricks) | Yes — Delta Sharing path delivers compressed Parquet directly from cloud object storage. Zero DBUs. | No. All queries route through the Databricks SQL warehouse. |
| Natural-language query | Available with a local LLM, a bring-your-own commercial model, or both. Row data never leaves the security perimeter; only schema metadata is sent to commercial models. | Roadmap line item (“AI integrations”) as of April 21, 2026. Deployment location, data handling, and timeline not yet published. |
| External user access | Yes — Databricks Delta Sharing recipients use a .share file; no Databricks workspace account required. | No. Every user needs a Databricks workspace account. |
| Client framework — Windows | VSTO (native COM integration) for maximum performance on large data writes. | Office Web Add-in (JavaScript / Office.js) on Windows, macOS, and the web. |
| Governance | Enforced by the source platform’s existing security model: Unity Catalog, Snowflake Horizon, Fabric OneSecurity. No parallel permission layer. | Unity Catalog — the same model Exponam uses for the Databricks path. |
| PivotTable creation | One-click at import. Available on the Windows edition. | Pivot Data checkbox at import; pivot-to-new-sheet only. |
01 · Platform coverage
The headline structural difference
The Databricks Excel Add-in connects to Databricks. By design, that is the full scope. Databricks is unlikely to build an Excel connector for Snowflake or Azure Fabric — no cloud-platform vendor can credibly occupy the cross-platform neutral position without commercial conflict with the platforms it does not own.
Exponam Analyst Intelligence is platform-neutral. It connects to Databricks and Snowflake today, with Microsoft Fabric and AWS Redshift in active development and Google BigQuery and the AtScale semantic layer on the near roadmap. A single ribbon, a single SQL scratchpad, a single natural-language interface, and a single governance posture sit above whichever platforms an organization actually uses.
For single-platform Databricks enterprises, this is not a deciding factor. For multi-cloud enterprises — and the share of large enterprises that fit that description is rising every quarter — it is the deciding factor. See Federation is not the same as neutrality for the structural argument.
02 · Cost structure
License versus consumption
The two products have fundamentally different cost shapes. Comparing them requires comparing license cost on one side against compute consumption on the other.
Exponam Analyst Intelligence is freemium up to 1M rows per query, with no time limit and no credit card. Enterprise licensing is volume-tiered per-user, per-month pricing with a $1,000 / month minimum. At 100 users the rate is $10 per user / month; at 10,000 users it steps down to $1.00; at 100,000 users to $0.50. Every dollar is visible in advance and budgetable. See the pricing page for the full schedule.
The Databricks Excel Add-in has no add-in license fee. Every query — task-pane import, embedded =DATABRICKS.Table() cell function, or formula-recalculation event in a shared workbook — runs against a Databricks SQL warehouse and consumes DBUs at the warehouse’s contracted rate. The license-versus-license comparison favors the Databricks Add-in. The license-versus-consumption comparison does not.
A specific risk in the Databricks model that does not exist in Exponam’s model: the shared-workbook recalculation event. Data imported via =DATABRICKS.Table() or =DATABRICKS.SQL() lives as a formula. Ordinary Excel recalculation — a third-party add-in, a Ctrl+Alt+F9, or a workbook reopen — can silently re-execute queries against a running warehouse. Exponam imports data as static cell values; refresh is managed from the ribbon, independently of Excel recalculation, and is never triggered by a recalc event.
For organizations evaluating both options on cost, the right exercise is to model expected DBU consumption against expected query volume at the contracted DBU rate, then compare to Exponam’s flat per-user line. Detailed worked numbers, including observed trial DBU consumption and a worked comparison at 100, 1,000, and 10,000 users, are in the full white paper.
03 · Data volume and performance
10,000,000 rows versus 948,650
Exponam Analyst Intelligence imports up to 10,000,000 rows per extract on an enterprise license, with no cap on the number of extracts a user can run. Benchmarked throughput on a standard Windows PC via the Delta Sharing path: one million rows delivered to Excel in approximately eleven seconds, driven by compressed Parquet transfer, Delta Lake partition optimization, and VSTO’s direct Excel object-model access on Windows.
In direct head-to-head testing against a 2.88M-row enterprise transaction dataset, both Exponam paths (Delta Sharing and SQL endpoint) returned the full dataset. The Databricks Excel Add-in returned approximately 948,650 rows and stopped with a non-descriptive error. Detailed methodology is in the white paper, and any organization planning to use either product for million-plus-row imports should validate against its own representative datasets before committing.
The technical reason Exponam clears the higher volume target on Windows is VSTO. Exponam’s VSTO add-in was architected by the co-author of the Microsoft Office COM integration layer and runs natively inside Excel as a .NET process with direct memory access to the Excel object model. The Databricks Add-in uses the Office Web Add-in framework on all platforms, including Windows — the same framework Microsoft recommends for cross-platform reach. For large-data writes, the Office.js API boundary introduces serialization overhead that VSTO does not.
For most workloads — interactive analysis, sub-million-row imports — both frameworks are entirely adequate. For high-volume imports on Windows, the architectural difference is real.
04 · Natural-language query and AI privacy
Shipping now vs. roadmap line item
Natural-language query is available in Exponam today. An analyst types a question in plain English, the system maps it to schema, constructs governed SQL, executes against the cloud platform, and returns results. The generated SQL is visible, reproducible, and auditable.
The privacy model behind that capability is the structural differentiator. Exponam supports two configurations:
- A fully local LLM — SQL-specialized models from 8B to 32B parameters, running on the analyst’s machine. No data, no schema, no tokens, and no query context leave the organization’s network. 8B models run efficiently on standard corporate laptops; 14B and 32B models deliver near-zero latency on GPU-equipped workstations. Model files are sourced from Hugging Face and verified as untampered with before loading.
- A bring-your-own commercial model — connect an existing OpenAI, Anthropic, or comparable contract. Exponam transmits only schema metadata; row-level data is never sent to the commercial provider.
The Databricks Excel Add-in announcement of April 21, 2026 names “AI integrations” as a roadmap item without published specifics on model deployment location, data handling, or timeline. When that capability ships and the details are published, this comparison row will be updated. Until then, privacy behavior cannot be evaluated against unpublished specifications.
For regulated industries — financial services, healthcare, the Big Four, pharmaceutical, government — the relevant distinction is not “AI available” versus “AI unavailable.” It is “AI that runs inside the security perimeter today” versus “AI that has not yet shipped, or that sends data to an external endpoint.” Today only one of the two products meets the first standard.
05 · Installation and deployment
A narrowed gap, with two real distinctions
The April 21 Databricks announcement materially narrowed the installation gap. Three paths are now available for the Databricks Add-in: Microsoft Office Marketplace (individual install with tenant permission), Microsoft 365 admin center central deployment (IT-administered), and the legacy XML-manifest sideload path retained from the Public Preview.
For self-service individual install in a permissive tenant, the Databricks Marketplace path is now comparably easy to Exponam’s single installer from exponam.com. Both products move from “decision made” to “first data in Excel” in minutes.
For managed enterprise tenants, the comparison comes down to deployment-tool fit:
- Exponam ships a custom MSI installer on enterprise licenses that slots into existing SCCM, Intune, or any standard Windows software-distribution pipeline. No tenant Marketplace approval is required.
- Databricks deploys through the Microsoft 365 admin center, which IT teams understand well, but which requires Marketplace vetting in most managed tenants and is subject to whatever security review the organization applies to all Marketplace add-ins.
For tenants that have disabled Marketplace add-ins by policy — common in financial services and regulated industries — the Databricks Add-in routes back through either central deployment or the legacy 10+-step sideload. The Exponam MSI path is not subject to Marketplace tenant policy.
For evaluations driven primarily by installation friction, both products will require IT involvement at enterprise scale. The comparison is which deployment pipeline fits the organization’s existing tooling better, not which product is easier in absolute terms.
06 · Governance, security, and data handling
Parity at source, structural differences above it
Both products enforce data governance at the source. For Databricks workloads, both rely on Unity Catalog for access control, row-level security, and audit trails — neither product maintains a parallel permission layer. On governance specifically, the two products are at parity for Databricks data.
Two structural differences are worth flagging.
Multi-platform governance. Exponam extends the same governance-at-source posture to Snowflake (via Snowflake Horizon) and to Microsoft Fabric (via OneSecurity). Unity Catalog metric views are a Databricks-specific construct that does not govern Snowflake or Fabric data. Enterprises that have standardized semantics in Unity Catalog have solved the semantic-consistency problem for their Databricks data; for multi-cloud environments, the cross-platform layer is still missing, and the Databricks Add-in does not address it.
Data transit. Exponam Analyst Intelligence is installed software, not a SaaS platform. No data, no schema definition, and no query ever transits Exponam-controlled infrastructure. The product is a direct bridge between the customer’s cloud platform and the analyst’s machine. For vendor-risk reviews, the assessment scope is correspondingly narrower than for a SaaS analytics product, and a SOC 2 attestation on the vendor’s cloud environment is not on the critical path — because the vendor’s cloud environment does not touch customer data.
Both products integrate with enterprise identity (Microsoft Entra ID, Okta) for authentication. Exponam’s security architecture, data-flow documentation, and NIST SP 800-218 attestation are published at the Security Center.
07 · Choosing between them
Where each product fits best
An honest comparison names the scenarios where each product is the better choice. Neither column is a concession; both are real fits.
Choose the Databricks Excel Add-in when…
Small teams operating daily inside a Databricks workspace. For a 40-person team that lives in Databricks notebooks and occasionally needs data in a spreadsheet, the Add-in is a competent, pragmatic choice. It avoids the $1,000 / month Exponam enterprise minimum. It provides Unity Catalog governance the team already knows.
Single-platform Databricks-only environments with no near-term multi-cloud plans. If Databricks is the entire data-platform footprint, the Databricks-only scope is not a limitation.
Workloads centered on SQL-scale queries rather than large imports. For analysts running SELECTs that return thousands or tens of thousands of rows, the row-capacity gap is not a deciding factor.
Vendor scale as the dominant evaluation criterion. Databricks is a $62B platform vendor; evaluators weighing balance-sheet stability will see the difference.
Choose Exponam Analyst Intelligence when…
Multi-cloud environments. Databricks plus Snowflake, Databricks plus Fabric, or any combination. Only Exponam covers more than one platform from a single Excel ribbon today.
Large enterprise deployments with non-technical user populations. Single installer, VSTO performance on Windows, MSI-based rollout independent of tenant Marketplace policy, ribbon-and-task-pane UI designed for business users.
Regulated industries with private-AI requirements. Financial services, healthcare, accounting firms, pharmaceutical, government. The fully local LLM option has no current Databricks equivalent.
Large-volume data imports. 10M-row ceiling, compressed Parquet path on Databricks, VSTO write performance on Windows.
External user access for data sharing. Partners, clients, regulators, vendors. Exponam’s Delta Sharing path on Databricks works with .share files without Databricks workspace accounts.
Cost-sensitive deployments at scale. Fixed per-user pricing rather than variable per-query compute. Zero DBUs on the Delta Sharing path. No formula-recalculation risk in shared workbooks.
Running Databricks ML models directly from Excel. Exponam’s Windows edition exposes Databricks ML Serving Endpoints as native Excel formulas via a guided formula builder.
Managed IT environments with MSI-based deployment. Exponam’s custom MSI fits existing SCCM and Intune pipelines without Marketplace vetting.
Frequently asked questions
Common questions about both products
Is there a Databricks Excel Add-in row limit?
Databricks is limited to one Excel worksheet. In trial testing against a 2.88M-row dataset, the Add-in returned approximately 948,650 rows before stopping with a non-descriptive error. Exponam Analyst Intelligence supports up to 10,000,000 rows per extract on an enterprise license. Any organization planning million-plus-row imports should validate against its own datasets before committing to either product.
Can the Databricks Excel Add-in connect to Snowflake or Microsoft Fabric?
No. The Databricks Excel Add-in is Databricks-only. For multi-cloud Excel access, only an independent vendor can credibly cover Snowflake, Microsoft Fabric, and Databricks from a single add-in. Exponam Analyst Intelligence covers Databricks and Snowflake today, with Microsoft Fabric and AWS Redshift in active development.
Does the Databricks Excel Add-in support natural-language query?
Not in the current product. Databricks listed “AI integrations” as a roadmap item without published specifics on model deployment, data handling, or timeline. Exponam Analyst Intelligence offers natural-language query today, with either a fully local LLM that keeps data inside the security perimeter or a bring-your-own commercial model configuration.
Does the Databricks Excel Add-in cost money?
There is no per-user license fee for the Add-in itself, but every query consumes Databricks DBUs at the warehouse’s contracted rate. Cell functions embedded in workbooks can re-execute on Excel recalculation events, adding compute consumption that is difficult to budget in advance. If/when Genie is enabled, all inquiries will also incur Genie compute in addition to SQL warehouse fees. Exponam Analyst Intelligence uses a fixed per-user license model with zero DBU consumption on the Delta Sharing path for Databricks data.
Can the Databricks Excel Add-in be deployed across an enterprise?
Yes. Microsoft 365 admin center central deployment is the supported path for managed environments, typically following Marketplace vetting and a security review. Self-service install from the Microsoft Office Marketplace is available where tenant policy permits it. Manifest files must be modified, locally deployed, shared, and trusted in the Office trust center. Exponam offers an additional path — a custom MSI installer for SCCM, Intune, or other standard Windows software distribution tooling — that does not require Marketplace vetting.
Can Excel users access Databricks data without a Databricks workspace account?
With the Databricks Excel Add-in, no. Every user requires a Databricks workspace account. With Exponam, yes — the Databricks Delta Sharing path uses .share files distributed to recipients who do not need Databricks workspace credentials. This is the standard solution for sharing governed Databricks data with external partners, clients, regulators, or contractors.
Does the Databricks Excel Add-in create PivotTables?
The Add-in offers a Pivot Data checkbox at import, which pivots to a new sheet only. Exponam Analyst Intelligence offers one-click PivotTable creation during the import workflow on the Windows edition.
Is Unity Catalog enforced by both products?
Yes. Both products enforce Databricks governance through Unity Catalog and do not maintain a parallel permission layer. If a user can see the data in Databricks, they can see it through either Excel add-in. If they cannot, neither will surface it.
What happens to costs in a shared workbook that gets recalculated?
With the Databricks Excel Add-in, cell functions such as =DATABRICKS.Table() and =DATABRICKS.SQL() can silently re-execute on Excel recalculation events — Ctrl+Alt+F9, a third-party add-in, or an ordinary workbook reopen. Each re-execution runs against a Databricks SQL warehouse and consumes DBUs. In workbooks that circulate across teams, this can add unbudgeted compute consumption. Exponam imports data as static cell values; refresh is managed from the ribbon and is unaffected by Excel recalculation events.
Can I try Exponam Analyst Intelligence before purchasing?
Yes. Exponam Analyst Intelligence is freemium. The free tier supports up to one million rows per query, has no time limit, and requires no credit card or registration. Download from the install page and connect to a Databricks Delta Share or a SQL endpoint in under five minutes.
Evaluate either product against your own data
The fastest way to compare is to install both and run them against representative datasets. Exponam Analyst Intelligence is free up to one million rows per query, with no time limit and no credit card.
Page last updated May 19, 2026. Reflects the Databricks Excel Add-in Public Preview release (March 2, 2026) and the Databricks product announcement (April 21, 2026). Exponam Analyst Intelligence specifications reflect the current generally available release.