Fusion
Sisense Fusion is a full-stack data analytics platform built around a proprietary high-performance analytics database called ElastiCube, which leverages in-chip technology for fast query response.
Publisher review
Sisense Fusion is a full-stack data analytics platform built around a proprietary high-performance analytics database called ElastiCube, which leverages in-chip technology for fast query response. It is designed for organizations that need to embed analytics into customer-facing applications, supporting cloud, on-premises, and hybrid deployments via Docker and Kubernetes. The platform targets companies with dedicated engineering teams who can manage the infrastructure and customization required, making it a strong fit for OEM scenarios and large-scale deployments. Sisense Fusion aims to bring actionable intelligence to both employees and customers, enabling all skill levels to analyze data and build customized analytic experiences within their workflows.
The core of Sisense Fusion is the ElastiCube engine, a columnar, in-memory data store that can handle terabytes of data and dozens of concurrent queries. It supports a wide range of data sources including cloud warehouses, relational databases, and APIs, but does not natively support unstructured or NoSQL data. The platform offers extensive APIs and SDKs for developer control, including iFrames, Embed SDK, and Sisense JS for embedding analytics. Advanced analytics features include natural language queries, forecasting, anomaly detection, and support for Python and R through notebooks. Sisense releases quarterly updates, with recent versions like L2025.3 (July 2025) and L2025.2 (April 2025), each receiving 12 months of support from release.
In the business intelligence market, Sisense Fusion competes directly with Tableau, Microsoft Power BI, Sigma, and Thoughtspot. While Power BI offers a low-code/no-code drag-and-drop interface with DAX and Power Query, Sisense requires SQL programming knowledge for data modeling and performance tuning. Tableau provides more polished out-of-the-box visualizations, whereas Sisense excels in embedded analytics and multi-tenant architecture. Sigma offers a spreadsheet-like interface for cloud data warehouses, while Thoughtspot emphasizes AI-driven search analytics. Sisense's strength lies in its developer-first philosophy and scalability, but it lacks the native AI insights and ease of use found in some competitors.
The honest trade-offs with Sisense Fusion include significant setup and technical expertise requirements, as ElastiCubes must be built and maintained with developer support and resource planning. It lacks native support for unstructured or NoSQL data, limiting use cases with varied data types. The platform has premium pricing, with self-hosted solutions starting at $10,000 per year and cloud pricing at least $21,000 per year for five users. Business users without technical backgrounds may find the learning curve steep unless data models are already curated. Customization often requires scripting, and out-of-the-box visual options may not match the polish of competitors like Tableau.
How it works
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ElastiCube engine
Proprietary columnar, in-memory database using in-chip technology for fast query response, handling terabytes of data and dozens of concurrent queries.
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Embedded analytics
Extensive APIs and SDKs including iFrames, Embed SDK, and Sisense JS for white-label embedding into customer-facing applications.
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Multi-tenant architecture
Supports scalable deployments with granular user roles (Admin, Data Admin, Designer, Data Designer, Viewer) and multi-level security.
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Advanced AI analytics
Features natural language queries, forecasting, anomaly detection, and Python/R notebook support for data scientists.
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Hybrid deployment
Deployable on any cloud, on-premises, or Sisense Cloud via Docker and Kubernetes, with support for hybrid dashboards.
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Data source connectivity
Connects to cloud warehouses, relational databases, APIs, and more, but lacks native support for unstructured or NoSQL data.
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Customizable visualizations
Web-based dashboard builder with custom widgets via BloX and JavaScript plugins, though customization often requires scripting.
Strengths and trade-offs
Strengths
- Excels in embedded analytics with extensive APIs and white-label options, making it a top choice for OEM scenarios.
- ElastiCube engine with in-chip technology delivers fast query performance on structured datasets up to terabytes in size.
- Multi-tenant architecture supports scalable deployments with granular user permissions and role-based access control.
- Offers advanced analytics features like natural language queries, forecasting, and anomaly detection for data-driven insights.
Trade-offs
- Requires significant setup and technical expertise, with ElastiCubes needing ongoing maintenance and resource planning.
- Does not natively support unstructured or NoSQL data, limiting use cases with varied data types like documents or logs.
- Premium pricing starts at $10,000 per year for self-hosted and $21,000 per year for cloud with five users, limiting small teams.
- Limited support for business users without technical backgrounds, as customization often requires scripting and SQL knowledge.
Pricing context
Self-hosted starts at $10,000 per year; cloud pricing starts at $21,000 per year for five users.
Getting started with Fusion
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Sign up for Sisense Fusion
Go to the Sisense website and choose a plan: self-hosted starting at $10,000/year or cloud starting at $21,000/year for five users. Complete the registration form, verify your email, and log into the platform to begin setup.
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Connect your data sources
In the admin panel, click Add Data Source. Select from supported cloud warehouses, relational databases, or APIs. Enter connection details like server address, credentials, and database name. Test the connection to ensure it succeeds before proceeding.
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Build an ElastiCube model
Open the ElastiCube Manager and choose the connected data source. Drag tables into the schema, define relationships between them, and set data types. Configure incremental refresh schedules to keep the cube updated without manual intervention.
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Create your first dashboard
Use the web-based dashboard builder to add widgets like charts or tables. Select fields from your ElastiCube, apply filters, and arrange visualizations on the canvas. Save the dashboard and share it with viewers by assigning roles in the permissions panel.
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Embed analytics into an app
Generate an embed code from the dashboard's share menu using the Embed SDK or iFrame. Copy the code into your application's HTML or JavaScript. Configure authentication and multi-tenant settings to restrict data access per user.
Frequently Asked Questions
What is Sisense Fusion?
Sisense Fusion is a full-stack data analytics platform built around the ElastiCube engine, a proprietary columnar, in-memory database using in-chip technology for fast query response. It is designed for embedding analytics into customer-facing applications and supports cloud, on-premises, and hybrid deployments.
How does Sisense Fusion's ElastiCube engine work?
The ElastiCube engine is a columnar, in-memory data store that leverages in-chip technology to handle terabytes of data and dozens of concurrent queries. It connects to cloud warehouses, relational databases, and APIs, but does not natively support unstructured or NoSQL data.
What are the key features of Sisense Fusion for embedded analytics?
Sisense Fusion offers extensive APIs and SDKs for white-label embedding, including iFrames, Embed SDK, and Sisense JS. It supports multi-tenant architecture with granular user roles and hybrid dashboards, making it ideal for OEM scenarios and large-scale deployments.
How much does Sisense Fusion cost?
Sisense Fusion self-hosted pricing starts at $10,000 per year, while cloud pricing starts at $21,000 per year for five users. This premium pricing targets organizations with dedicated engineering teams and may be prohibitive for small teams.
What are the main differences between Sisense Fusion and Tableau?
Sisense Fusion excels in embedded analytics and multi-tenant architecture, while Tableau offers more polished out-of-the-box visualizations. Sisense requires SQL knowledge for data modeling, whereas Tableau provides a more intuitive drag-and-drop interface for business users.
What are the weaknesses of Sisense Fusion?
Sisense Fusion requires significant setup and technical expertise, with ElastiCubes needing ongoing maintenance. It lacks native support for unstructured or NoSQL data, and its premium pricing starts at $10,000 per year. Business users may find the learning curve steep without curated data models.
Alternatives
How Fusion compares
Direct head-to-head against 2 competitors. Picked by 7wData.
Fusion
- Pricing
- Self-hosted starts at $10,000 per year; cloud pricing starts at $21,000 per year for five users.
- Target
- Sisense Fusion is a full-stack data analytics platform built around a proprietary high-performance analytics database called ElastiCube, which leverages in-chip technology for fast query response.
- Strength
- Excels in embedded analytics with extensive APIs and white-label options, making it a top choice for OEM scenarios.
- Watch for
- Requires significant setup and technical expertise, with ElastiCubes needing ongoing maintenance and resource planning.
Plasticity
- Pricing
- Custom/Contact sales
- Target
- 3D modeling and design
- Deployment
- Desktop
- Strength
- Intuitive UI and fast rendering
- Watch for
- Limited CAM and simulation features
FreeCAD
- Pricing
- Free
- Target
- Open-source CAD users
- Deployment
- Desktop
- Strength
- Full-featured parametric modeling
- Watch for
- Steeper learning curve for beginners
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