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Keep Sisense if it already works for your internal BI. The move is for the customer-facing layer.
No published Databrain case study replaced Sisense, so this is the closest evidence we have: two teams that replaced another BI tool (Looker, Metabase) for customer-facing analytics. Figures and quotes are taken from each published case study. Two customers is a small sample.
Contract management SaaS, replaced Looker
“We now offer our customers extensive insights out of the box, sparing them the pain of creating their own metrics, all while ensuring they have a seamless experience.”
Freight pricing platform, replaced Metabase
“Databrain allowed us to create a fully custom analytics module. Anybody in the org was now able to create metrics and share data with their tool”
The short version of Databrain and Sisense side by side.
| Databrain | Sisense | |
|---|---|---|
| Built for | Multi-tenant B2B SaaS products embedding customer-facing analytics | An analytics platform with a data engine, semantic layer, AI suite and embedding, for embedded and internal use |
| How it embeds | Web components (Shadow DOM) for React, Next.js, Angular, Vue, Svelte, Solid and vanilla JS | Iframe, Embed SDK, Sisense JS or Compose SDK |
| How tenants are scoped | clientId in a server-minted guest token; one data app serves every tenant | One of three models: self-contained tenants, a deployment per tenant, or user groups with data security rules |
| Query model | Live queries against your warehouse | Live connections, the ElastiCube database, or a hybrid |
| AI for end users | Natural-language search on every plan, follow-up chat on Pro and Enterprise | Assistant, search, narratives, forecast and pulse alerts, with Sisense's managed LLM or your own |
| Deployment | Databrain cloud, or self-hosted on Enterprise | Sisense SaaS, your own cloud (AWS, Azure, GCP) or on-prem on Enterprise |
| Pricing model | Flat and published: $999/mo Growth, $1,995/mo Pro, Enterprise custom | Self-serve and Enterprise plans; no amounts on the plans page |
| Typical time to production | 1 to 4 weeks in our published case studies; SpotDraft 4 weeks, Freightify 1 week | Sisense's plans page gives no figure |
Databrain is an AI-native embedded analytics platform for B2B SaaS. You connect your warehouse with read-only access, define metrics, mint a guest token from your backend, and place a web component in your app.
Dashboards are white-labeled, and customers can ask questions in natural language.
Sisense is an analytics platform with a data engine that can connect live to your warehouse, build ElastiCube databases, or do both, plus a semantic layer, dashboards, an AI suite called Sisense Intelligence, and four ways to embed. For OEM use it documents three multi-tenancy models.
Its plans page lists an Enterprise plan, with SaaS, own-cloud or on-prem deployment, and a self-serve plan with a free trial.
In Sisense a tenant is whatever the model you pick makes it: an organization tenant with its own login URL and admin, a whole separate deployment, or a user group on shared content with row-level rules. In Databrain a tenant is the clientId in a guest token, and one data app serves all tenants. Sisense's options go further on isolation; Databrain's is one pattern with less to operate.
Sisense is data-engine and semantic-model first: live connections or ElastiCube, perspectives over a central model, and a semantic layer that its AI is grounded in. Databrain is metric-builder first: drag and drop, custom SQL or natural language, then a token.
Sisense documents an iframe it describes as not dynamic or customizable, an Embed SDK that wraps the iframe, Sisense JS for embedding without iframes, and Compose SDK for building queries and charts from code. Databrain offers one embed, web components, configured through four theming layers. Compose SDK goes further if you want to compose your own visualizations.
Sisense lists an Enterprise plan and a self-serve plan and publishes no amounts on its plans page. Databrain is a flat monthly price by feature, with unlimited seats, embeds and tenants.
Sisense is the broader platform: 200+ connectors, an MCP server for external AI tools, a longer compliance list, and a 99.99% Premium SLA on Enterprise. Databrain is a narrower embedding layer, which is the point if embedding is all you need.
Twenty-one capabilities that decide a customer-facing analytics build, Databrain against Sisense. Sisense cells cite Sisense's own documentation and website, opened on 22 October 2026. Databrain cells cite our pricing page, product docs and Trust Center. Where Sisense is stronger, the cell says so.
| Capability | Databrain | Sisense |
|---|---|---|
| Embedding and branding | ||
| Yes: Web components in your page | Yes: Iframe, Embed SDK, Sisense JS, Compose SDK | |
| Whether the analytics surface is part of your page or a document your page hosts. | <dbn-dashboard> and <dbn-metric> from @databrainhq/plugin render inside Shadow DOM. An iframe route exists and our docs mark it as not recommended. | Sisense documents four ways to embed. The iframe is described as easy and fast to deploy but not dynamic or customizable. Embed SDK wraps the iframe and adds events and commands. Sisense JS embeds dashboards, widgets and filters without iframes. Compose SDK builds queries, charts and filters from your application code. |
| Configure through component options | Yes: Compose SDK builds queries and charts in codeSisense leads here | |
| If your design needs a visualization neither product ships, Sisense's SDK gives you more room. | You configure the embed through the component options and four theming layers, rather than composing new visualizations from primitives. | Compose SDK creates Sisense queries, charts and filters from application code, with no predefined dashboards required, or renders existing widgets by ID. You can use Sisense components, customize them, or bring your own charts and UI libraries. Sisense's comparison table rates its flexibility High, against Medium for Embed SDK. |
| Yes: Seven framework guides | Yes: Compose SDK for React, Angular, Vue | |
| How much glue code your team writes per framework. | Guides for React, Next.js, Angular, Vue, Svelte, Solid and vanilla JS, all against the same component. | Sisense's developer docs say Compose SDK supports TypeScript with React, Angular and Vue, and needs a Sisense Linux instance on L2022.10 or later. Sisense's embedding page still says Compose SDK currently supports TypeScript and React, and lists L2022.11 as the minimum, so check the version you would run. Embed SDK is a JavaScript library. |
| Yes: Four theming layers, per-customer themes | Yes: White labeling, enabled by licence | |
| Whether "matches our design system" is a token map or a configuration page. | Chart appearance, admin theme options, custom chart settings and saved metric settings resolve in a fixed priority order. White-labeling and custom UI themes per customer are on every plan; email white-labeling is on Pro and Enterprise. | White labeling must be enabled in your licence. It covers logos, favicon, page title, login and activation text, the user menu links, and emails, set through the admin UI or the REST API. A "Powered by Sisense" label can be hidden only if your licence allows it. The docs page is marked for the Grow and Enterprise tiers and for Classic mode only. Sisense's plans page lists full white-labeling on Enterprise. |
| Server-minted guest token with an expiry | SSO, with a third-party cookie caveat | |
| Customer-facing embeds need an auth path that survives browser cookie changes. | Your backend mints the guest token with an expiry time. Databrain validates every request: token lookup, expiry, the request origin against your allowed domains, and permissions. | Sisense's embedding docs warn that browsers disabling third-party cookies may break embedded solutions and say Sisense has prepared methods to avoid it; we did not review that page. Sisense's plans page lists SSO and an SSO Router on Enterprise. |
| Multi-tenancy and security | ||
| Yes: One data app, scoped by clientId | Yes: Three documented models, Enterprise tier | |
| Whether adding a tenant is a value in a token or a model you chose and operate. | One data app serves every tenant, and you do not need a data app per tenant. Tenancy can be a shared table with a tenant column, or a schema or database per tenant. Most teams run a single workspace. | Self-contained adds a tenant hierarchy on one deployment with complete separation between tenants. Multi-instance runs separate deployments on separate servers. Internal capabilities uses user groups, shared data models and dashboards, and row-based security. Sisense's docs mark multitenancy as a premium feature, available only in the Sisense managed cloud or self-hosted. |
Pass a clientId | Depends on the model; self-contained creates a tenant | |
| The per-tenant step your onboarding automation has to perform. | A new tenant's data is scoped as soon as your backend mints a guest token with its clientId, provided your tenant column, schema or database mapping covers it. | In the self-contained model a main-tenant admin creates each organization tenant, which gets its own login URL and a Tenant Admin. Each tenant needs at least one admin, so the number of tenants on one deployment is limited to the number of admins in your licence. In the OEM architectures built on user groups, a group is typically created per tenant and that tenant's data models and dashboards are shared with it. |
| Partial: Shared dashboards; variants are copies | Yes: Per-tenant SSO, branding, data modelsSisense leads here | |
| If every customer needs their own models, SSO or look, Sisense's isolated models give you that natively. | By default every tenant sees the same dashboards, scoped by the guest token. Per-customer themes are on every plan. For per-customer layouts, Databrain documents a master dashboard with client dashboards derived from it, provisioned through the Import Dashboard API or the MCP server. Import and clone are copy operations: later edits to the master do not propagate to client dashboards already created. | In the self-contained and multi-instance models each tenant has dedicated SSO and its own white labeling, and tenants can create data models and dashboards that are private to them. In the internal-capabilities model, branding is one configuration shared by all tenants and tenants cannot reach the data model. |
| Yes: Tenant filter injected into the SQL | Yes: Data security rules per user or group | |
| Both are real row-level security. The difference is where the rule lives and who maintains it. | For builder metrics Databrain injects the tenant filter into the generated query server-side. Custom SQL metrics are not auto-injected: the author references the tenant variable, or the metric runs unscoped. Per-session constraints go in rlsSettings in the guest token, enforced server-side and fixed at mint time. A separate row and column level security feature is listed on Enterprise. | Rules control which rows of a data model each user or group can see, and a single dashboard shows different results to each. Rules propagate across table relationships. Rules can be inclusionary or exclusionary and the most restrictive combination wins. Sisense documents support for up to 1450 values in the result set of a dimension, and in some cases up to 3500. |
| Yes: Table, schema or database per tenant | Yes: Shared model, dedicated models, or dedicated servers | |
| Matters when a customer's contract requires their data on separate infrastructure. | Tenants can share tables with a tenant column on every table, or each tenant can have its own schema or database, referenced in metric SQL through a database-name variable. | Sisense's OEM guide describes shared data models with row-based security, dedicated data models and dashboards per tenant, dedicated ElastiCubes per client with shared dashboards through the Dynamic ElastiCube plugin, and a dedicated Sisense server per tenant. It notes limits on ElastiCubes per machine, and that tenants on a shared server share resources. |
| Partial: SOC 2, GDPR; ISO 27001 in progress | Yes: ISO 27001 and 27701, SOC 2 Type 2, HIPAA, GDPR, CCPASisense leads here | |
| If a buyer's procurement list names ISO 27001, ISO 27701, HIPAA or CCPA, Sisense lists them and Databrain does not yet. | Databrain's Trust Center lists SOC 2 and GDPR as compliant and ISO 27001 as in progress. Our pricing page lists HIPAA as coming soon on Pro and Enterprise. Ask for the current report before you rely on any of them. | Sisense says it undergoes regular independent audits for ISO 27001, ISO 27701, SOC 2 Type 2, HIPAA, GDPR and CCPA, and runs a Trust Center. Its embedded analytics page also cites ISO 42001. Its plans page lists HIPAA readiness and column-level security on Enterprise. |
| Yes: Cloud, or self-hosted on Enterprise | Yes: SaaS, own cloud or on-prem; 99.99% SLASisense leads here | |
| Regulated customers ask where the data sits and what uptime is contracted. | Cloud, or self-hosted in your own infrastructure on Enterprise, with VPC peering and a bastion host. Queries run against your warehouse and Databrain stores metadata such as dashboard definitions and metric configuration, not your business data. If you turn on caching, query results are cached in Databrain's managed Redis or in a Redis you run. | Sisense's Enterprise plan lists deployment on SaaS, on your own cloud (AWS, Azure, GCP) or on-prem, with a 99.99% Premium SLA, auto-scaling and 30-day backup written into the contract. Databrain's Enterprise SLA is 99.5% uptime. |
| Data and semantic layer | ||
| Partial: Live queries; caching on Pro and up | Yes: Live, ElastiCube, or hybridSisense leads here | |
| If you want data held in a fast engine instead of queried live, Sisense offers it. | Queries run live against your warehouse. Caching is available on Pro and Enterprise, using Databrain's managed Redis or your own. | Sisense offers live connections to warehouses such as Snowflake, Amazon Redshift, Google BigQuery and Azure Synapse without data duplication, ElastiCube as a high-performance analytical database that combines multiple sources, and a hybrid of in-memory caching with warehouse depth. |
| Yes: Warehouses and databases, live | Yes: 200+ connectorsSisense leads here | |
| Confirm your exact sources in both lists before you commit. | Databrain's pricing page names Snowflake, BigQuery, Redshift, Databricks, ClickHouse, Postgres, MySQL, MSSQL, Athena, Trino, MongoDB and Elasticsearch. Growth includes one data source; Pro and Enterprise are unlimited. | Sisense lists 200+ connectors, its modeling page says it connects cloud, on-prem systems and third-party apps, and Enterprise adds advanced connectivity such as SSH and VPN. |
| Partial: Semantic layer on Enterprise | Yes: Semantic layer, perspectives, notebooksSisense leads here | |
| Governed metric definitions across many tools are Sisense's core strength. | Datasets, datamarts and the semantic layer are listed under Data studio on the Enterprise plan. On Growth and Pro, metrics are built directly with the builder or custom SQL. A Python and SQL environment is on every plan. | Sisense defines metrics, relationships and business meaning in a governed semantic layer, adds semantic enrichment that generates table and column descriptions, offers Perspectives as sub-models inheriting from a central model, and embeds Jupyter notebooks with SQL, Python and R. |
| Yes: Forecasting on Pro, more on Enterprise | Yes: Forecast, pulse alerts, narrative, explanation | |
| Both cover the common cases. Check the specific functions against your roadmap. | Drill-down and forecasting are on Pro and Enterprise. Forecasting, outlier detection, predictive algorithms and recommendations are listed on Enterprise. | Sisense Intelligence lists Forecast to project trends, Pulse to alert on anomalies, Narrative to turn charts into plain-language summaries, and Explanation to surface the drivers behind changes. |
| What your customer gets | ||
| Yes: Natural-language search on every plan | Yes: Assistant, search, narratives, MCPSisense leads here | |
| Sisense's AI surface is broader. Databrain's natural-language search is included on every plan. | Natural-language search is included on every plan, and follow-up chat on Pro and Enterprise. Connect OpenAI, Azure OpenAI, Claude, Gemini, Llama or Mixtral. | The Sisense assistant answers questions in natural language inside dashboards, shows how it interpreted each question, and can turn answers into charts. It uses Sisense's managed LLM or your own. An admin enables it per tenant and per user group, with monthly AI credit budgets per tenant and group. It works on iframe-embedded dashboards. Sisense lists an MCP server so external AI tools can reach governed models. Its docs list limits: it cannot save new calculated fields, cannot modify existing widgets, supports timestamps only down to days, and is described as not yet ready for complex data models. |
| Partial: Enterprise plan | Yes: Drag-and-drop reports and explorationSisense leads here | |
| Whether every customer request for a new chart becomes a ticket for your team. | End-user report creation is an Enterprise feature, and also needs the workspace and permissions configured to allow it. | Sisense lists self-serve analytics with drag-and-drop reports, filters and data exploration in the embed, and users with design permissions can add assistant-generated widgets to dashboards. |
| Token and API management | Yes: REST API, Git workflows, playgroundSisense leads here | |
| Relevant if you manage analytics through a release pipeline. | Server-to-server API keys mint guest tokens, and dashboards can be provisioned through the Import Dashboard API or the MCP server. | Sisense offers a REST API for data, data models and security, a Compose SDK playground for React, Angular and Vue, and its data modeling page cites Git workflows. |
| Commercial | ||
| Yes: Flat and published | Self-serve and Enterprise, no amounts | |
| One of these bills is a number you can read today; the other starts with a quote. | Growth $999/mo, Pro $1,995/mo, Enterprise custom. Seats, embeds and tenants are unlimited on every plan. Pricing is by module, not by seats, monthly active users, query volume or capacity units. | Sisense's plans page lists a self-serve plan for startups and growing teams, with a free trial, and an Enterprise plan reached through a demo or contact request. It publishes no amounts. |
| 14-day trial; 99.5% SLA on Enterprise | Free self-serve trial; 99.99% SLA on EnterpriseSisense leads here | |
| Check what the support tier you can afford actually includes. | 14-day free trial, with a proof of concept on your dataset for Pro and Enterprise. Support is Slack, MS Teams, Google Spaces and in-app chat on every plan. Enterprise adds 24x7 premium support, a 99.5% uptime SLA and a dedicated account manager. | Sisense's self-serve plan offers "Try free". Enterprise lists premium support, a dedicated customer success manager, Sisense engineers working alongside your team, and a 99.99% Premium SLA. |
Tenant isolation is the hardest part of customer-facing analytics, and Databrain and Sisense solve it in different places. Sisense gives you a choice of models, from a tenant hierarchy to a separate deployment per tenant. Databrain puts it in the token and the generated query.
Your backend mints a guest token that carries the tenant clientId. The embed sends that token with each request. Databrain looks it up server-side, checks expiry, permissions and the allowed origin, then generates SQL with the tenant filter applied before the query reaches your warehouse. One data app serves every tenant, and extra per-session constraints go in rlsSettings.
One sharp edge: in custom SQL metrics the tenant filter is not auto-injected, so the author must reference the tenant variable. A custom metric that omits it runs unscoped.
Databrain's Trust Center lists SOC 2 and GDPR as compliant and ISO 27001 as in progress; HIPAA is listed as coming soon on our pricing page. Compare the lists above against your buyers' requirements.
Sisense documents three ways to do multitenancy. Self-contained adds a tenant hierarchy on one deployment, with complete application-level separation, a separate login URL per tenant, per-tenant SSO and white labeling, and a Tenant Admin role. Multi-instance runs completely separate deployments on separate servers. Internal capabilities uses user groups, shared data models and dashboards, and row-based security.
The trade-offs are Sisense's own. Self-contained tenants on shared infrastructure can be isolated onto their own nodes with Data Groups. Multi-instance gives the highest isolation; for a dedicated server per tenant Sisense's OEM guide lists low resource utilization, high hardware costs and complicated asset change management as the disadvantages. Internal capabilities has low hardware costs, but all users log in through the same URL, share one branding configuration, and tenants share server resources.
Multitenancy is a premium feature, available only in the Sisense managed cloud or self-hosted. Each self-contained tenant needs at least one admin, so the tenant count is limited to the admins in your licence.
Sisense's trust page lists ISO 27001, ISO 27701, SOC 2 Type 2, HIPAA, GDPR and CCPA.
clientId and your data app name.POST /api/v2/guest-token/createBoth are real tenant isolation; the difference is whether you choose and operate a tenancy model or pass a value in a token.
Both lists are genuine. If your situation matches the Sisense side, that is the right call.
Match your situation to the row, then check the feature comparison for the detail.
| If your question is | Lean toward | Because |
|---|---|---|
| The viewer is your customer, not your colleague | Databrain | Customer-facing embedding, per-customer themes and no per-viewer cost are what Databrain is built for. |
| Many tenants with self-serve onboarding | Databrain | Tenant scope comes from a guest token, and one data app serves all tenants. |
| The dashboard must match your product UI | Databrain | Web components and four theming layers. Sisense supports white labeling too, so check both against your design system. |
| You need a governed semantic layer and a data engine shared across tools | Sisense | Live connections, ElastiCube and a semantic layer are Sisense's core, and Databrain's modeling is simpler. |
| You need to build fully custom visual components | Sisense | Compose SDK builds queries and charts from code in React, Angular or Vue. |
| Each customer needs its own data models, SSO or deployment | Sisense | Sisense's self-contained and multi-instance models give each tenant its own SSO and white labeling, or its own server. |
| You need ISO 27001, ISO 27701, HIPAA or CCPA on the vendor's list | Sisense | Sisense lists them. Databrain's Trust Center lists SOC 2 and GDPR as compliant and ISO 27001 as in progress; HIPAA is listed as coming soon on our pricing page. |
| You need forecastable spend from a published price | Databrain | A flat monthly plan with unlimited seats, embeds and tenants. |
| You need to self-host the analytics layer | Either | Both offer it on their Enterprise tier. Sisense lists SaaS, your own cloud or on-prem; Databrain lists self-hosted with VPC peering and a bastion host. |
A flat plan and a plan list with no amounts are different shapes of bill, and Sisense publishes no amounts on its plans page, so compare Databrain and Sisense against a quote at your own tenant count. Neither is cheaper in every case.
Growth includes multi-tenancy and 1 data source. Pro adds unlimited data sources, SSO and roles and permissions. Enterprise adds self-hosting, multi-region deployment, VPC peering and bastion host, and a dedicated account manager.
Sisense's self-serve plan is described as embedding with iframe or Compose SDK, with built-in AI for natural-language queries and auto-narratives. Its Enterprise plan adds native multi-tenant architecture, SaaS, own-cloud or on-prem deployment, column-level security, bring-your-own LLM, full white-labeling, premium support and a dedicated customer success manager.
Sisense publishes no prices, so the rows read as stated on its plans page. We do not estimate a Sisense price. Databrain prices are from the pricing page. Both were read on 22 October 2026.
Keep Sisense for internal reporting if it works there. The move is for the customer-facing layer. Our published customers went live in 1 to 4 weeks, SpotDraft in 4 and Freightify in 1, and you can run both side by side until you cut over.
List the highest-traffic dashboards and the metrics behind them in your Sisense data model.
Connect to Databrain with read-only access.
Choose how tenants are separated: a tenant column, or a schema or database per tenant.
Rebuild them as Databrain metrics, using drag and drop, custom SQL or natural language.
From your backend, create a token with each customer's clientId.
Replace the Sisense embed with a Databrain web component for a pilot group and run both.
Move the remaining tenants, then retire the Sisense tenants or deployments you no longer need.
Plan to recreate dashboards rather than import them: we document no automated Sisense importer. No published Databrain customer has migrated from Sisense. The range comes from our published case studies, none of which replaced Sisense.
Yes, for customer-facing analytics inside a SaaS product. Databrain renders as web components, scopes each tenant from a guest token and charges a flat monthly plan. It is not a replacement for Sisense as an internal analytics platform with a data engine and a shared semantic layer, so keep Sisense for that if you rely on it.
Sisense's plans page lists a self-serve plan with a free trial and an Enterprise plan, and publishes no amounts. Databrain is flat and published: $999 per month for Growth and $1,995 for Pro, with unlimited seats, embeds and tenants. Ask Sisense for a quote at your tenant count and compare it with the Databrain plan that fits.
Sisense documents three models: self-contained tenants on one deployment, separate deployments per tenant, and user groups with row-level rules on shared content. Databrain has one pattern: you pass a clientId in a guest token and one data app serves all tenants. Sisense's options go further on isolation and per-tenant customization; Databrain's is less to choose and operate.
No. Sisense's connectivity page lists live connections to warehouses such as Snowflake, Redshift, BigQuery and Azure Synapse, the ElastiCube database, and a hybrid of the two. Databrain queries your warehouse live, with caching on Pro and Enterprise.
Yes. Databrain includes white-labeling and per-customer themes on every plan. Sisense documents white labeling that must be enabled in your licence, and lists full white-labeling on Enterprise. Compare both against your design system before you decide.
Yes, on their Enterprise tiers. Sisense's Enterprise plan lists SaaS, your own cloud (AWS, Azure, GCP) or on-prem. Databrain offers self-hosting on Enterprise, with VPC peering and a bastion host.
Yes. Sisense Intelligence includes an assistant, search, narratives, explanations, forecasts and pulse alerts, with Sisense's managed LLM or your own, and an MCP server for external AI tools. Databrain includes natural-language search on every plan and follow-up chat on Pro and Enterprise, with your choice of LLM.
Databrain's published customers went live in 1 to 4 weeks. SpotDraft replaced Looker in 4 weeks and Freightify replaced Metabase in 1, according to their published case studies. No published customer has switched from Sisense, so treat this as Databrain's published range, not a Sisense migration benchmark.
We check every Sisense claim against Sisense's own public documentation and website, and we date the check: every Sisense source below was opened on 22 October 2026. Sisense's plans page is at sisense.com/plans, and sisense.com/pricing redirects there. Sisense's docs mark features with Launch, Grow and Enterprise tiers that its plans page does not name, so we cite the plan the vendor names and flag where a doc page marks a tier.
Databrain claims come from our published pricing page, product documentation, Trust Center and customer case studies. Sisense publishes no prices on its plans page, so we do not state a Sisense price or a Sisense implementation time. Where we found no Sisense documentation of a capability, the cell says so, not that it is impossible. We did not review Sisense's support terms beyond the plans page, its Third-Party Cookies page, or any certification beyond the vendor's own list.
Where Sisense is stronger, we say so. If you find something here that is out of date or wrong, tell us and we will fix it.
Thirty minutes. Bring your architecture and your warehouse, and we will show a white-labeled dashboard running against your schema and tell you plainly if you are a bad fit.