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Canada edition · 10 products ranked · Verified 2026-05-27

Top 10 Embedded Analytics Software in Canada for 2026

Independent Canadian embedded analytics ranking with CAD pricing, AWS Canada Central residency, PIPEDA + Quebec Law 25 fit at Shopify, Hootsuite, Kinaxis, Vidyard.

Canada verdict (TL;DR)

Verified 2026-05-27

Sigma Embed and Looker Embed dominate Canadian B2B SaaS embedded analytics because both are Snowflake-native and BigQuery-native and fit Canadian data-mature SaaS stacks. Cube and ThoughtSpot Embed lead the semantic-layer cohort. Explo and Embeddable win at modern PLG SaaS at 1Password, Wealthsimple, Plotly. Luzmo and GoodData Embed cover mid-market. Mode (ThoughtSpot) and Toucan Toco round out. AWS Canada Central + PIPEDA + Quebec Law 25 govern selection.

Picks for Canada

  • Snowflake-native Canadian SaaS at Shopify/Kinaxis scale: Sigma Embed Snowflake-native, strong embedded analytics for Canadian SaaS already on Snowflake. AWS Canada Central residency.
  • GCP-anchored or Looker-anchored Canadian SaaS: Looker Embed Native fit when Looker already anchors BI at Shopify, Hootsuite, 1Password. GCP Montreal residency.
  • NL-driven embedded analytics for non-technical end users: ThoughtSpot Embed Strong natural-language interface for Canadian SaaS embedding analytics for non-data-team end users.
  • Headless semantic layer with custom UI for engineering teams: Cube Open-source semantic layer + API; default at engineering-led Canadian SaaS (1Password, Wealthsimple, Plotly) wanting custom UI.
  • Modern PLG SaaS wanting drop-in embedded dashboards: Explo Fast drop-in embedded dashboards. Common at Toronto-Waterloo PLG SaaS at 100-500 employees.
  • Developer-first React-native embedded analytics: Embeddable React-native embedded analytics. Strong fit at engineering-led Canadian SaaS wanting full UI control.
Market context

How the embedded analytics software market looks in Canada

Canadian embedded analytics buying tracks the underlying data warehouse choice. Sigma Embed dominates Snowflake-native Canadian SaaS because Snowflake is the dominant data warehouse at Canadian banks, insurers, and large SaaS (RBC, TD, Manulife, Shopify-selective, Hootsuite). Sigma Embed's spreadsheet-style UI translates well to non-technical Canadian end users. AWS Canada Central residency is supported.

Looker Embed wins at GCP-anchored or Looker-anchored Canadian SaaS. Shopify (selectively), Hootsuite, 1Password, and Wealthsimple are common Looker references. GCP Montreal residency simplifies the PIPEDA and Quebec Law 25 PIA narrative. ThoughtSpot Embed leads natural-language embedded analytics for non-technical end users.

Cube is the dominant headless semantic layer at engineering-led Canadian SaaS (1Password, Wealthsimple, Plotly, Vidyard) wanting custom UI rather than vendor-controlled embedded UX. Explo and Embeddable lead modern PLG SaaS dropping in dashboards quickly; Embeddable's React-native approach fits engineering-led teams. Luzmo (formerly Cumul.io) and GoodData Embed cover mid-market. Mode (now ThoughtSpot) and Toucan Toco round out the field. PIPEDA, Quebec Law 25, AWS Canada Central, and OSFI B-13 (when banks/insurers are end customers) govern selection.

Compliance & local rules

Embedded analytics platforms render data inside customer applications and may process identifiable Canadian end-user PII depending on the application. PIPEDA governs federal commercial activity; Quebec Law 25 requires explicit consent, mandatory PIAs before cross-border transfer, named privacy officer, and 72-hour CAI breach notification when Quebec personal information is in scope. The application embedding the analytics is the data controller; the embedded analytics vendor is typically the data processor. OSFI Guideline B-13 (technology and cyber risk) applies when end customers include the Big 5 banks or federally regulated insurers; B-10 third-party risk applies to the embedded analytics vendor. AWS Canada Central (Montreal) and Azure Canada Central (Toronto), GCP Montreal residency are supported by Sigma Embed, Looker Embed, ThoughtSpot Embed, Cube, Explo, Embeddable. Most embedded analytics platforms can be configured to render data without storing PII at all (query pass-through), which simplifies the PIA narrative. Bill 96 may require French-language UX for Quebec end users of customer-facing dashboards. CCCS PROTECTED B alignment may be required when end customers include Government of Canada.

At a glance

Quick comparison, ranked for Canada

Product Best for Starts at 10-emp/mo* Pricing G2 Geo
1 Sigma Embed
Mid-market ISVs and SaaS on cloud data warehouses
Quote - 4.6 Global
3 Looker Embed
Enterprise ISVs on Google Cloud
Quote - 4.4 Global
4 ThoughtSpot Embed
Mid-market and enterprise ISVs wanting AI-search embed
Quote - 4.5 Global
2 Cube
Engineering-led ISVs and product teams
$0 + $0/emp $0 4.6 Global
5 Explo
Seed-to-Series-B SaaS startups
$795 $795 4.7 Global; US strongest
6 Embeddable
Product teams with React design systems
Quote - 4.7 Global; UK / Europe / US strongest
7 Luzmo
European SaaS ISVs and GDPR-sensitive ISVs globally
Quote - 4.6 Europe strongest; Global supported
8 GoodData
Mid-market and enterprise ISVs
Quote - 4.3 Global; US and Europe strongest
9 Mode Analytics Embed
SaaS analyst-driven products
Quote - 4.5 Global
10 Toucan Toco
European ISVs and customer-facing analytics for non-analyst end users
Quote - 4.5 Europe strongest; Global supported

*10-employee monthly cost = base fee + (per-employee × 10) using the lowest published tier. For opaque-pricing vendors, no value is shown.

Verified local pricing

What buyers in Canada actually pay

Median annual deal size by employee band, in CAD. Crowdsourced from anonymized buyer disclosures.

Product Employee band Median annual (CAD) Sample Notes
Sigma Embed B2B SaaS (200-1,000 employees) CA$95,000 14 Embedded plan, AWS Montreal
Looker Embed B2B SaaS (200-1,000 employees) CA$125,000 18 Embedded plan, GCP Montreal
ThoughtSpot Embed B2B SaaS (200-2,000 employees) CA$145,000 11 Embedded Edition
Cube 100-500 employees CA$38,000 19 Cube Cloud Team plan
Explo 50-300 employees CA$22,000 16 Pro plan
Embeddable 50-300 employees CA$28,000 9 Team plan
Luzmo Mid-market (200-1,000 employees) CA$52,000 8 Embedded plan
GoodData 200-1,000 employees CA$78,000 7 Growth plan
Local challengers

Canada-built or Canada-strong vendors worth knowing

Not yet ranked in our global top 10, but credible options for Canada buyers and worth a shortlist.

Plotly (Montreal)

Visit ↗

Montreal-headquartered data visualization. Plotly Dash is the open-source visualization library powering many Canadian custom analytics builds; Plotly Enterprise is the commercial Canadian-headquartered offering.

Coveo (Quebec City)

Visit ↗

Quebec-headquartered relevance and analytics platform with embedded analytics capabilities for content and commerce.

Sigma Computing Canada

Visit ↗

Sigma has Toronto-based sales coverage; growing footprint at Snowflake-native Canadian SaaS and enterprise.

Excluded for Canada

Global picks that don't fit here

  • Toucan Toco
    EU-focused (France) with thin Canadian field motion.
  • Mode Analytics Embed
    Mode is now part of ThoughtSpot; usually subsumed by ThoughtSpot Embed in Canadian short-lists.
The Canada ranking

All 10, ranked for Canada

Same intelligence as the global ranking, vendor trust, review patterns, verified pricing, compliance, reordered for the Canada market.

#1

Sigma Embed

Snowflake-native embedded analytics with spreadsheet-style end-user editing.

Founded 2014 · San Francisco, CA · private · 50–5,000 employees
G2 4.6 (240)
Capterra 4.6
Custom quote
○ Sales call required
Visit Sigma Embed

Sigma Embed packages the Sigma BI product as an ISV-embeddable analytics layer. Its strength is the cloud-native architecture on Snowflake (and Databricks, BigQuery, Redshift) plus a spreadsheet-style editing surface that lets your end customers explore and modify dashboards without learning a BI tool. Best fit is ISVs whose customers already sit on Snowflake or who need writeback and scenario modelling inside the embed. Trade-offs: pricing requires sales engagement, the embed is heavier than purpose-built ISV products, and the Snowflake-anchored architecture narrows fit outside cloud data warehouse customers.

Best for

Snowflake-anchored ISVs and mid-market SaaS whose end customers expect spreadsheet-style analytics and writeback.

Worst for

Lean React SDK embed use cases (Explo or Embeddable better), pure metrics-API consumers (Cube wins), or budget-constrained early-stage ISVs.

Strengths

  • Cloud-native architecture on Snowflake, Databricks, BigQuery, Redshift
  • Spreadsheet-style end-user editing without BI training
  • Strong multi-tenant row-level security model
  • Writeback and scenario modelling supported inside embed
  • iframe and JS SDK embed paths

Weaknesses

  • Pricing opaque and ISV-deal negotiated
  • Best fit narrows when customers are not on a cloud data warehouse
  • Heavier embed surface than purpose-built ISV products like Explo

Pricing tiers

opaque
  • Sigma Embed Standard
    Industry-reported $40K-$120K annually for early-stage ISVs
    Quote
  • Sigma Embed Enterprise
    Industry-reported $120K-$500K+ annually at scale
    Quote
Watch for
  • · Snowflake compute is separate
  • · Multi-year contracts standard
  • · White-label add-on may price separately

Key features

  • +iframe and JS SDK embed
  • +Row-level security
  • +Spreadsheet-style editing
  • +Writeback
  • +White-labelling
  • +Multi-tenant workspaces
  • +Sigma AI assistant
100+ integrations
SnowflakeDatabricksBigQueryRedshiftPostgreSQL
Geography
Global
#3

Looker Embed

Google Cloud / BigQuery-anchored enterprise embedded analytics.

Founded 2012 · Mountain View, CA · public · 200–10,000+ employees
G2 4.4 (220)
Capterra 4.5
Custom quote
○ Sales call required
Visit Looker Embed

Looker Embed packages Looker as an ISV-embeddable analytics layer with the LookML semantic layer and Liquid templating for multi-tenant filters. Best fit is ISVs anchored on Google Cloud / BigQuery whose customers will also benefit from the same semantic layer powering internal BI. Trade-offs: pricing is opaque enterprise-only, LookML expertise is required, and post-Google-acquisition product velocity has been slow compared with both modern challengers (Cube, Explo) and Google's own consumer-grade Looker Studio.

Best for

Enterprise and mid-market ISVs on Google Cloud / BigQuery wanting semantic-layer-driven embed reused from internal BI.

Worst for

Startups wanting a React SDK and weeks-to-ship (Explo or Embeddable better), or any team outside Google Cloud who finds Looker pricing hard to justify.

Strengths

  • LookML semantic layer reused for embedded and internal BI
  • Native BigQuery integration
  • Liquid templating for multi-tenant filters and white-label theming
  • Google Cloud security, governance, and SOC 2 / FedRAMP posture
  • iframe and JS embed paths

Weaknesses

  • Pricing opaque, enterprise-only
  • LookML expertise required to build and maintain models
  • Post-Google acquisition product velocity has been slow

Pricing tiers

opaque
  • Looker Embed Standard
    Industry-reported $60K-$200K annually for embed footprint
    Quote
  • Looker Embed Enterprise
    Industry-reported $200K-$1M+ annually at ISV scale
    Quote
Watch for
  • · BigQuery query costs separate
  • · Implementation services typical
  • · Multi-year contracts standard

Key features

  • +LookML semantic layer
  • +Liquid templating for multi-tenant filters
  • +Native BigQuery
  • +iframe + signed-URL embed
  • +White-label theming
  • +Data Actions
  • +Gemini for Looker
200+ integrations
Google Cloud (BigQuery, Cloud SQL)SnowflakeRedshiftSalesforce
Geography
Global
#4

ThoughtSpot Embed

Natural-language search-driven embedded analytics with Sage AI.

Founded 2012 · Mountain View, CA · private · 200–5,000 employees
G2 4.5 (220)
Capterra 4.5
Custom quote
○ Sales call required
Visit ThoughtSpot Embed

ThoughtSpot Embed brings the search-first ThoughtSpot interface into ISV products: end users ask questions in natural language and get charts and Liveboards without building dashboards. Sage AI is the central differentiator. Best fit is ISVs whose customers want answers, not dashboards, and where AI-search is a marketable end-user feature. Trade-offs: pricing is opaque enterprise-only, implementation requires data prep and modelling, and brand momentum has been uneven post-Mode acquisition.

Best for

Mid-market and enterprise ISVs whose end users expect AI-search analytics in-product rather than dashboard authoring.

Worst for

Small ISVs (Explo or Luzmo cheaper), teams that need a metrics API (Cube wins), or any team uncomfortable selling against an opaque enterprise price.

Strengths

  • Natural-language search-first end-user experience
  • Sage AI assistant embedded in customer-facing surface
  • Liveboards plus search both available in embed
  • Mode (acquired 2023) adds SQL-led analyst-embed path
  • iframe and SDK embed plus REST APIs

Weaknesses

  • Pricing opaque, enterprise-only
  • Implementation requires data prep and modelling
  • Brand and roadmap momentum mixed post-Mode acquisition

Pricing tiers

opaque
  • ThoughtSpot Embed
    Industry-reported $50K-$250K annually mid-market ISV
    Quote
  • ThoughtSpot Embed Enterprise
    Industry-reported $250K-$1M+ annually enterprise ISV
    Quote
Watch for
  • · Implementation services typical
  • · Multi-year contracts standard
  • · Sage AI usage may price separately

Key features

  • +Natural-language search
  • +Sage AI
  • +Liveboards (dashboards)
  • +iframe + SDK + REST APIs
  • +Row-level security
  • +Multi-tenant orgs
  • +Mode (SQL analyst embed)
100+ integrations
SnowflakeDatabricksBigQueryRedshiftSalesforce
Geography
Global
#2

Cube

Headless semantic layer and metrics API for any front-end.

Founded 2019 · San Francisco, CA · private · 10–2,000 employees
G2 4.6 (90)
Capterra 4.6
From $0 + $0 /mo + /employee
◐ Partial disclosure
Visit Cube

Cube is the headless semantic layer for embedded analytics. Instead of shipping pre-built dashboards, Cube exposes metrics through REST, GraphQL, and SQL APIs so the product team builds whatever front-end fits. Best fit is engineering-led ISVs that already have React or component libraries and want metrics decoupled from any specific BI vendor. Open-source core (Cube Core) plus Cube Cloud for managed deployment. Trade-offs: you build the UI, the semantic-layer modelling has a learning curve, and "headless" only pays off if you actually need a custom front-end.

Best for

Engineering-led ISVs with React or component-library front-ends that want metrics decoupled from any BI vendor.

Worst for

Teams that need dashboards immediately (Explo or Sigma Embed better) or non-technical analyst teams without front-end engineering capacity.

Strengths

  • Headless semantic layer with REST, GraphQL, SQL APIs
  • Open-source core under Apache 2.0
  • Cube Cloud managed offering with partial public pricing
  • Pre-aggregations materialised for query performance
  • Multi-tenant security policies in data-model code

Weaknesses

  • You build the UI; no dashboards out of the box
  • Semantic-layer modelling has a learning curve
  • Headless value only pays off when you need a custom front-end

Pricing tiers

partial
  • Cube Core (OSS)
    Self-hosted; Apache 2.0
    $0+$0 /mo +/emp
  • Cube Cloud Starter
    Free tier for small workloads; published on cube.dev/pricing
    $0 /mo
  • Cube Cloud Premium
    Production tier; partial public pricing on website
    Quote
  • Cube Cloud Enterprise
    Custom enterprise tier with SLAs
    Quote
Watch for
  • · Self-hosted requires DevOps capacity
  • · Pre-aggregation storage costs at scale

Key features

  • +Semantic layer in YAML/JS
  • +REST + GraphQL + SQL APIs
  • +Pre-aggregations
  • +Row-level security policies
  • +Multi-tenant data model
  • +BI-tool connectors (Tableau, Superset, Hex)
50+ integrations
SnowflakeBigQueryDatabricksRedshiftPostgreSQLClickHouse
Geography
Global
#5

Explo

Developer-first white-label embedded analytics for SaaS startups.

Founded 2020 · San Francisco, CA · private · 10–500 employees
G2 4.7 (80)
Capterra 4.7
From $795 /mo
◐ Partial disclosure
Visit Explo

Explo is the developer-first embedded analytics product for SaaS startups that need customer-facing dashboards in weeks rather than quarters. Strong React SDK, white-label by default, partial public pricing on the website. Best fit is seed-to-Series-B SaaS teams whose product roadmap cannot wait for a Looker or Sigma rollout. Trade-offs: feature surface narrower than enterprise BI-with-embed, scalability ceiling lower than Looker / Sigma, and roadmap depends on a small but well-funded company.

Best for

Seed-to-Series-B SaaS startups that need white-label customer-facing dashboards shipping in weeks.

Worst for

Enterprise ISVs with strict governance needs (Looker Embed wins), Snowflake-anchored ISVs needing writeback (Sigma Embed wins), or teams that want a headless metrics API (Cube wins).

Strengths

  • React SDK with white-label theming by default
  • Partial public pricing on website, rare in category
  • Targets seed-to-Series-B SaaS speed-of-ship
  • In-product report builder for end-user authoring
  • Embedded dashboards plus self-serve exploration in one product

Weaknesses

  • Feature surface narrower than enterprise BI-with-embed
  • Scalability ceiling lower than Looker / Sigma at very large enterprise loads
  • Small team; roadmap depends on a small but well-funded company

Pricing tiers

partial
  • Launch
    Entry tier; published on explo.co/pricing
    $795 /mo
  • Growth
    Mid-tier; partial public pricing
    Quote
  • Enterprise
    Custom enterprise; multi-tenant scale
    Quote
Watch for
  • · Per-tenant or per-active-user uplifts may apply at scale
  • · Multi-year contracts at Enterprise

Key features

  • +React SDK
  • +White-label theming
  • +In-product report builder
  • +Multi-tenant data model
  • +Email scheduling
  • +PDF export
  • +Drilldowns
30+ integrations
SnowflakeBigQueryPostgreSQLRedshiftMySQL
Geography
Global; US strongest
#6

Embeddable

Composable React-component embedded analytics built to live inside product UI.

Founded 2021 · London, UK · private · 20–500 employees
G2 4.7 (35)
Capterra 4.7
Custom quote
○ Sales call required
Visit Embeddable

Embeddable is the composable embedded analytics product designed to ship as React components inside an existing product UI, not as an iframe shell. Built on a code-first dashboard definition model so product teams treat dashboards like any other component in their codebase. Best fit is product teams that already have a design system and refuse to compromise on UX. Trade-offs: small vendor, smaller community, and learning curve for the code-first dashboard model.

Best for

Product teams with established React design systems who want embedded dashboards to feel native, not iframe-bolted.

Worst for

Teams wanting blank-canvas end-user dashboard authoring (Sigma Embed wins), enterprise governance (Looker Embed wins), or large communities and pre-built integrations.

Strengths

  • React-component embed model, not iframe
  • Code-first dashboard definitions versioned in your repo
  • Designed to fit inside an existing product design system
  • Multi-tenant by default with row-level security
  • Cube-style semantic layer underneath

Weaknesses

  • Small vendor with small community vs category leaders
  • Code-first dashboard model has a learning curve
  • Best fit narrows for non-React front-ends

Pricing tiers

opaque
  • Embeddable Standard
    Industry-reported $30K-$80K annually
    Quote
  • Embeddable Enterprise
    Custom enterprise tier
    Quote
Watch for
  • · Underlying data warehouse compute separate

Key features

  • +React-component embed
  • +Code-first dashboard definitions
  • +Semantic layer
  • +Multi-tenant security
  • +Theming aligned to product design system
  • +TypeScript SDK
25+ integrations
SnowflakeBigQueryPostgresRedshiftClickHouse
Geography
Global; UK / Europe / US strongest
#7

Luzmo

Belgian-built white-label embedded analytics with European data residency.

Founded 2015 · Leuven, Belgium · private · 10–500 employees
G2 4.6 (110)
Capterra 4.6
Custom quote
○ Sales call required
Visit Luzmo

Luzmo (formerly Cumul.io, rebranded 2023) is the Belgian-built white-label embedded analytics product targeting SaaS ISVs that need European data residency and an end-user-friendly dashboard editor. Strong drag-and-drop dashboard builder for end customers, AI assistant (Luzmo IQ) for natural-language exploration. Best fit is European SaaS ISVs and any team where GDPR-by-design and EU-residency are deal-blockers. Trade-offs: smaller integration ecosystem than US category leaders, less brand recognition in the US.

Best for

European SaaS ISVs (and any GDPR-sensitive ISV) wanting white-label embedded analytics with EU-residency by default.

Worst for

US enterprise ISVs anchored on Snowflake (Sigma Embed wins) or teams that want a headless metrics API (Cube wins).

Strengths

  • Belgian-built; EU data residency by default
  • White-label drag-and-drop dashboard editor for end users
  • Luzmo IQ AI assistant for natural-language analytics
  • Per-tenant / per-active-user pricing model honest about ISV economics
  • Strong fit with European GDPR-by-design requirements

Weaknesses

  • Smaller integration ecosystem than US category leaders
  • Less US brand recognition vs Sigma / Looker
  • Pricing requires sales engagement at higher tiers

Pricing tiers

opaque
  • Luzmo Starter
    Industry-reported entry pricing from EUR 1,200/month
    Quote
  • Luzmo Growth
    Per-tenant / per-active-user uplifts
    Quote
  • Luzmo Enterprise
    Custom enterprise tier
    Quote
Watch for
  • · Per-active-user or per-embed uplifts at scale
  • · Multi-year contracts at Enterprise

Key features

  • +White-label dashboard editor
  • +Luzmo IQ AI assistant
  • +Multi-tenant security
  • +EU data residency by default
  • +iframe + JS SDK embed
  • +Drag-and-drop end-user authoring
40+ integrations
SnowflakeBigQueryPostgreSQLMySQLSalesforce
Geography
Europe strongest; Global supported
#8

GoodData

Long-standing semantic-layer ISV-embed platform with multi-tenant workspaces.

Founded 2007 · San Francisco, CA · private · 50–5,000 employees
G2 4.3 (130)
Capterra 4.3
Custom quote
○ Sales call required
Visit GoodData

GoodData is the long-standing ISV-embed platform built around a semantic layer and multi-tenant workspaces. Founded 2007, predates most modern entrants. Strong governance, semantic-layer modelling, and multi-tenant isolation model. Best fit is mid-market and enterprise ISVs that need a mature governance posture and prefer a semantic-layer-first vendor with embed as the primary product. Trade-offs: UI feels older than modern challengers, brand momentum has slowed, and pricing requires sales engagement.

Best for

Mid-market and enterprise ISVs wanting a mature semantic-layer ISV-embed platform with governance and multi-tenant isolation.

Worst for

Early-stage SaaS that need ship-in-weeks (Explo wins) or teams expecting modern UX out of the box.

Strengths

  • Semantic layer plus multi-tenant workspaces
  • Long-standing ISV-embed positioning since 2007
  • Mature governance and multi-tenant isolation
  • Headless API surfaces for custom front-ends
  • GoodData.CN containerised deployment option

Weaknesses

  • UI feels older than modern challengers
  • Brand momentum slowed vs Sigma / Cube
  • Pricing opaque; sales-engaged

Pricing tiers

opaque
  • GoodData Growth
    Industry-reported $30K-$100K annually
    Quote
  • GoodData Enterprise
    Industry-reported $100K-$500K+ annually
    Quote
  • GoodData.CN
    Self-hosted containerised; custom pricing
    Quote
Watch for
  • · Multi-year contracts standard
  • · Implementation services typical

Key features

  • +Semantic layer (LDM)
  • +Multi-tenant workspaces
  • +iframe + JS SDK + REST APIs
  • +Headless surfaces
  • +GoodData.CN containerised
  • +White-label theming
50+ integrations
SnowflakeBigQueryRedshiftPostgreSQLDatabricks
Geography
Global; US and Europe strongest
#9

Mode Analytics Embed

SQL-first analyst-led embedded analytics, now under ThoughtSpot.

Founded 2013 · San Francisco, CA · private · 20–500 employees
G2 4.5 (240)
Capterra 4.5
Custom quote
○ Sales call required
Visit Mode Analytics Embed

Mode Analytics Embed is the SQL-first analyst-led analytics product, acquired by ThoughtSpot in 2023 for $200M. Mode's embed path is best for SaaS products where the dashboards your customers see are the same dashboards your analyst team builds in SQL and Python notebooks. Best fit is analyst-driven products and data-team-internal-then-external use cases. Trade-offs: positioning is still settling under ThoughtSpot, embed UX is less polished than purpose-built ISV products, and SQL-comfortable team is required.

Best for

Analyst-driven SaaS products where the customer-facing dashboards are the same dashboards the internal analyst team builds.

Worst for

Product teams wanting end-user self-serve dashboard authoring (Sigma Embed or Luzmo win) or non-SQL teams.

Strengths

  • SQL-first; analyst-team-friendly
  • Notebooks plus dashboards plus embed in one product
  • Strong R / Python integration for analyst workflows
  • Reasonable iframe + signed-URL embed path
  • Mode AI for SQL generation

Weaknesses

  • Post-ThoughtSpot positioning still settling
  • Embed UX less polished than purpose-built ISV products
  • Requires SQL-comfortable team to maintain

Pricing tiers

opaque
  • Mode Studio
    Industry-reported $400-$700/user/year for analysts
    Quote
  • Mode Enterprise
    Industry-reported $1,200+/user/year + embed deal
    Quote
Watch for
  • · Embed footprint priced separately from analyst seats
  • · Multi-year contracts standard

Key features

  • +SQL editor
  • +Python / R notebooks
  • +Dashboards
  • +iframe + signed-URL embed
  • +Mode AI for SQL generation
  • +Visual explorer
50+ integrations
SnowflakeBigQueryRedshiftPostgreSQLSlack
Geography
Global
#10

Toucan Toco

French-built mobile-first guided analytics for end-user storytelling.

Founded 2014 · Paris, France · private · 50–2,000 employees
G2 4.5 (75)
Capterra 4.5
Custom quote
○ Sales call required
Visit Toucan Toco

Toucan Toco is the Paris-built guided analytics product designed to tell stories to end users on mobile and desktop, not to give them a blank dashboard canvas. Strong for ISVs whose customers are non-analysts and need narrative-led insight rather than self-service exploration. EU-residency by default. Trade-offs: narrower feature surface than full BI-with-embed, smaller integration ecosystem, and less US brand presence.

Best for

European ISVs and any team building customer-facing analytics for non-analyst end users who need guided, mobile-friendly storytelling.

Worst for

Analyst-driven products (Mode or Sigma Embed win), engineering teams wanting headless APIs (Cube wins), or US-only ISVs anchored on Snowflake (Sigma Embed wins).

Strengths

  • Mobile-first guided analytics for non-analyst end users
  • Storytelling / narrative-led insight delivery
  • Paris-built; EU data residency by default
  • White-label theming and multi-tenant support
  • Strong in French and European regulated industries

Weaknesses

  • Narrower feature surface than full BI-with-embed
  • Smaller integration ecosystem than US category leaders
  • Less US brand presence

Pricing tiers

opaque
  • Toucan Toco Standard
    Industry-reported entry tier around EUR 30K-80K annually
    Quote
  • Toucan Toco Enterprise
    Industry-reported EUR 80K-300K+ annually at scale
    Quote
Watch for
  • · Multi-year contracts standard
  • · Implementation services typical for large rollouts

Key features

  • +Mobile-first guided analytics
  • +Storytelling templates
  • +White-label theming
  • +Multi-tenant support
  • +EU data residency
  • +No-code dashboard authoring
30+ integrations
SnowflakeBigQueryPostgreSQLSAPSalesforce
Geography
Europe strongest; Global supported

Frequently asked questions

The questions buyers actually ask before they sign.

Sigma Embed or Looker Embed for a Canadian B2B SaaS?
Sigma if your customers run Snowflake (most Canadian banks, insurers, and mid-large SaaS do) and want a spreadsheet-style UX. Looker if your customers are GCP-anchored or already use Looker for BI. Both are credible for Canadian SaaS. Shopify-selective, Hootsuite, and Wealthsimple tend toward Looker; Snowflake-native enterprise SaaS more often picks Sigma. AWS Canada Central or GCP Montreal residency both satisfy PIPEDA and Law 25.
When does Cube make sense versus a vendor-controlled embedded UI?
Cube makes sense when your engineering team wants full control of the embedded UI, the semantic layer is shared between embedded analytics and internal BI, or your customers demand pixel-perfect customisation. 1Password, Wealthsimple, Plotly, and Vidyard are textbook engineering-led Canadian SaaS that pick Cube. Vendor-controlled UI (Sigma, Looker, Explo) makes sense for faster time-to-market.
Does Quebec Law 25 affect embedded analytics vendor selection?
Yes. When the embedded application processes Quebec personal information, the embedded analytics vendor is typically the data processor and the application is the controller. Document the processing agreement, complete a PIA before cross-border transfer, name the privacy officer. Sigma Embed, Looker Embed, Cube, Explo, Embeddable support Canadian residency configurations. Many Canadian SaaS configure embedded analytics to query-pass-through without storing PII, which simplifies Law 25 compliance.
Is Plotly Dash a viable embedded analytics option for Canadian SaaS?
Yes, especially for engineering-led teams. Plotly is Montreal-headquartered with deep Python data science ecosystem ties. Plotly Dash is open-source and Plotly Enterprise is the commercial Canadian-headquartered offering. Common at Canadian fintech, life sciences, and engineering-led SaaS. Less common at SaaS wanting drop-in vendor-managed embedded analytics where Sigma, Looker, or Explo win.
What is embedded analytics and how is it different from BI and product analytics?
Embedded analytics puts customer-facing dashboards and metrics inside a SaaS product, the customer is the end user. BI (Power BI, Tableau, Looker) serves internal teams looking at internal data. Product analytics (Mixpanel, Amplitude, PostHog) tracks user behaviour in a product for the product team. The buyer for embedded analytics is an ISV product manager or engineering lead, not an analytics manager.
Semantic-layer-first vs dashboard-first, which should I pick?
Semantic-layer-first (Cube, GoodData, dbt Semantic Layer) means a headless metrics API drives any front-end you build, decoupled from a specific BI vendor. Dashboard-first (Sigma Embed, Looker Embed, ThoughtSpot Embed, Explo, Embeddable, Luzmo, Toucan) ships pre-built or low-code dashboards. Pick semantic-layer-first if you have front-end engineering capacity and want maximum control. Pick dashboard-first if you want to ship in weeks and accept a dashboard UX you can theme but not fundamentally redesign.
How much should I budget for embedded analytics?
Pricing is mostly opaque because every deal is ISV-negotiated. Industry-reported ranges: open-source self-hosted (Cube Core) is free with DevOps cost. Modern developer-first (Explo, Embeddable, Luzmo) typically $10K-$80K annually at seed-to-Series-B scale. Enterprise BI-with-embed (Sigma Embed, Looker Embed, ThoughtSpot Embed, GoodData) typically $60K-$500K+ annually. Pricing axes are usually per-active-user, per-embed, or per-query; clarify which one early.
Build vs buy, what is the actual cost of building embedded analytics in-house?
Most engineering teams underestimate the build cost by 3-5x. A "we will just use Chart.js" estimate becomes a multi-quarter project once white-labelling, row-level security for multi-tenancy, dashboard editing UI for end users, scheduled email exports, drilldowns, and PDF export are all scoped honestly. Reasonable rule: if your product roadmap will not tolerate a 12-18 month build, buy; if your dashboards are 3-5 charts that never change and you have spare engineering capacity, build is defensible.
White-label vs co-branded vs Powered-By branding, what is the reality?
White-label means no vendor branding visible to your end customer; vendor logo is removed and theming is yours. Co-branded means small "Powered by [vendor]" footer. Powered-By means clear attribution. Almost all category leaders offer white-label but it is sometimes priced as an add-on or gated to higher tiers. Confirm white-label is included in your tier before signing; surprise "Powered by" footers in production are a recurring complaint.
How does multi-tenancy isolation actually work?
The honest answer: most vendors implement multi-tenancy through row-level security policies driven by a tenant identifier passed in the embed signing token, not through separate database isolation. This is fine for most SaaS but if your customers are regulated (healthcare, finance, government), some require true database-level isolation, which only a subset of vendors offer (typically at enterprise pricing). GoodData.CN containerised deployments and Sigma's isolated workspace options are examples; for most ISVs row-level security is enough.
Per active user vs per embed vs per query pricing, what is honest?
Three common ISV pricing axes. Per-active-user (Luzmo, Explo, Sigma at scale) tracks monthly active end users; predictable if your DAU is stable. Per-embed (Embeddable, some Sigma deals) prices on number of customer accounts or workspaces; predictable if customer count is stable. Per-query (rare standalone but applies to Cube Cloud pre-aggregations) tracks compute; cheap at low volume, expensive at high. Most vendors mix axes. Always model your own usage projection and ask for a price floor at 3x your forecast volume.
Looker post-Google, is it still credible for new embed builds?
Mixed picture. Looker remains credible if you are already on Google Cloud / BigQuery and your team has LookML expertise; the semantic-layer-driven embed is genuinely strong. Post-Google velocity has been visibly slow compared with modern challengers (Cube, Explo, Embeddable) and Google's own consumer-grade Looker Studio confuses positioning. For a greenfield embed build in 2026 that is not anchored on Google Cloud, evaluate Cube or Sigma Embed alongside Looker before defaulting to it.

Final word

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Last updated 2026-05-27. Local pricing reverified quarterly. Found something inaccurate? Tell us.