Used For

• +**Your Tableau dashboards take 10 minutes to load with real data** → Sisense's elastic model handles terabytes without slowing down
• +**You're copying data between databases, spreadsheets, and cloud services manually** → Automated data blending pulls everything together in one place
• +**Your app needs charts but building them from scratch would take months** → Embed interactive dashboards with their SDK in weeks
• +AI forecasting that actually works - predicts patient volumes, holiday demand, inventory needs
• +Natural language queries - ask "show me Q3 sales trends" instead of writing SQL

Best For

• >Your current BI tool crashes every time you hit it with real data volumes
• >You're building an app and need to embed charts without becoming a data visualization expert
• >Finance team is manually blending 12 different data sources and it's taking forever

Not For

• -Teams under 50 people — you're paying enterprise prices for overkill when Google Sheets would work fine
• -Companies wanting plug-and-play simplicity — this needs dedicated setup time and data expertise
• -Budget-conscious startups — the custom pricing model means you're probably looking at $10k+ per year minimum

Pairs With

• *PostgreSQL (or whatever database you're pulling massive datasets from that break other BI tools)
• *AWS (where your data lake lives and Sisense connects to pull everything together)
• *React (to embed the dashboards into your actual app using their SDK)
• *dbt (for data transformations before Sisense turns it into pretty charts)
• *Slack (where your team gets alerts about forecasts and dashboard updates)
• *Salesforce (as one of many data sources you're blending for complete customer views)

The Catch

• !No public pricing means you're stuck in the "schedule a demo for a quote" dance with their sales team
• !Despite the "no-code" marketing, you'll need someone who understands data modeling or you'll hit walls fast
• !Works great for big data but it's expensive overkill if you're just making basic reports from small datasets

Bottom Line

Built for companies drowning in terabytes of data who need analytics that actually scale instead of choking.