DataBrain vs Embeddable

DataBrain is an embedded analytics platform for B2B SaaS product and engineering teams. It adds multi-tenant, white-label dashboards and natural-language analytics inside a software product. Data can come from Snowflake, BigQuery, Redshift, Databricks, Postgres, spreadsheets, and web APIs. Teams define versioned, auditable metrics with a Visual Builder, Custom SQL, or AI Chat Mode. Embedding options include React, Angular, Vue, Next.js, iframes, and web components; developers can also use the npm package and REST API guest tokens. DataBrain says every query is scoped by tenant key, with row and column rules enforced at the query layer. It stores metadata while data remains in the customer’s warehouse, with data-residency options. The maker describes GDPR compliance, SOC 2 auditing, ISO 27001 certification, HIPAA readiness with optional BAA, CCPA support, AES-256 storage encryption, and SSL/TLS in transit.

Embeddable is a developer toolkit for adding customer-facing analytics to applications. Teams can create interactive dashboards, self-serve analytics, and AI-powered insights on a governed foundation. Dashboards are embedded through an HTML web component and server-side token, without an iframe. Components, data models, themes, and dashboards can remain in a version-controlled repository and be pushed with the SDK. Teams may assemble dashboards in a no-code builder or define them in code. AI chat accepts plain-language questions and returns text or live charts grounded in a semantic layer, with row-level security applied. Embeddable queries a customer database directly and says it does not store a copy. Deployment choices include managed Cube hosting, self-hosted Cube Core, or Cube Cloud; managed hosting offers EU and US options. The company states SOC 2 Type II certification and GDPR compliance, with read-only transactions, SSL/TLS connections, and AES-128 protection for SSH or database credentials. During proof of concept, supported onboarding includes an account manager plus frontend and data-engineering resources. Pricing is a project-scoped monthly subscription quoted after scoping.