Sisense Fusion

Basic Information

Sisense Fusion is an AI-driven analytics platform designed to embed intelligence directly into business workflows and applications. It combines business intelligence with AI to analyze data across multiple systems, delivering contextual insights.

• Model: Sisense Fusion (encompasses Fusion Analytics and Fusion Embed)
• Version: Sisense releases quarterly updates. Recent versions include L2025.3 (July 2025), L2025.2 (April 2025), L2025.1 (January 2025), L2024.3 (October 2024), L2024.2 (July 2024), and L2024.1 (May 2024).
• Release Date: Sisense Fusion was initially announced on February 9, 2021.
• Minimum Requirements:
  • Server:
    • Windows Server: 2008 R2, 2012, 2016, 2019, 2022 (64-bit).
    • Linux: Red Hat Enterprise Linux 7+, CentOS 7+, Ubuntu 16.04+, Debian GNU/Linux 8.0+, Oracle Linux 6.5+, Amazon Linux AMI, Fedora 12+, Suse Linux 11+ (x86-64/AMD64 architectures).
  • Client: Any operating system supporting modern HTML5-compatible web browsers (Windows, macOS, Linux, iOS, Android).
• Supported Operating Systems:
  • Server: Windows Server (2008 R2, 2012, 2016, 2019, 2022) and various 64-bit Linux distributions (e.g., RHEL, CentOS, Ubuntu, Debian, Oracle Linux, Amazon Linux, Suse Linux).
  • Client: Windows, macOS, Linux, iOS, Android (via modern web browsers).
• Latest Stable Version: Sisense follows a quarterly release cycle. As of November 2025, recent stable versions include L2025.3 (released July 2025) and L2024.3 (released October 2024).
• End of Support Date: Each Sisense version receives 12 months of support from its release date. For example, L2025.3 (July 2025 release) is supported until September 2026, and L2024.3 (October 2024 release) is supported until December 2025.
• End of Life Date: Not explicitly stated as a single date; tied to the 12-month support cycle per version.
• Auto-update Expiration Date: Not explicitly stated. Security Bearer Tokens, used for integrations, can have expiration dates, and tokens without an expiration date may expire upon upgrading to newer versions (L2024.1 and later).
• License Type: Sisense offers an End User License Agreement for internal business purposes and an OEM License Agreement for embedding Sisense Software into customer products. Pricing is typically subscription-based, often per user or based on usage metrics like data volume and compute power.
• Deployment Model: Cloud-native architecture supporting deployment on any cloud (e.g., AWS, Azure), on-premises, or Sisense Cloud. It supports single or multi-tenant deployments.

Technical Requirements

Sisense Fusion is a robust analytics platform with varying requirements depending on deployment scale and type (server vs. client).

• RAM: 16 GB recommended for server environments.
• Processor: 2.0 GHz i7 dual-core processor recommended. Sisense supports x86-64/AMD64 architectures.
• Storage: 2 GB required, with more space for additional voices and data. An SSD drive is recommended.
• Display: Client-side access requires a minimum resolution of 1280x800 pixels.
• Ports: Standard TCP/IP network protocols are required. HTTPS (port 443) is typically used for secure client-server communication and cloud deployments.
• Operating System:
  • Server: 64-bit Windows Server (2008 R2, 2012, 2016, 2019, 2022) or various 64-bit Linux distributions (e.g., RHEL 7+, CentOS 7+, Ubuntu 16.04+).
  • Client: Any OS supporting modern web browsers (Windows, macOS, Linux, iOS, Android).

Analysis of Technical Requirements

Sisense Fusion's technical requirements reflect its enterprise-grade nature, supporting both Windows and a wide range of Linux server environments. The emphasis on 64-bit systems and recommended specifications like 16GB RAM and i7 processors indicate its design for handling complex data processing and analytical workloads. Client-side access is highly flexible, relying on modern web browser compatibility, which minimizes specific OS requirements for end-users. The platform's cloud-native architecture further allows for scalable infrastructure provisioning, adapting to demand rather than fixed hardware.

Support & Compatibility

Sisense Fusion offers comprehensive support and broad compatibility to integrate into diverse enterprise environments.

• Latest Version: Sisense releases quarterly updates, with the latest versions including L2025.3 (July 2025) and L2024.3 (October 2024).
• OS Support:
  • Server: 64-bit Windows Server (2008 R2 through 2022) and numerous Linux distributions (e.g., RHEL, CentOS, Ubuntu, Debian, Oracle Linux, Amazon Linux, Suse Linux) on x86-64/AMD64 architectures.
  • Client: Compatible with modern HTML5 browsers across Windows, macOS, Linux, iOS, and Android.
• End of Support Date: Each version is supported for 12 months after its release date, ensuring continuous access to updates and patches.
• Localization: Not explicitly detailed in search results, but a global user base suggests multi-language support is likely.
• Available Drivers: Sisense connects to a wide range of data sources, including cloud warehouses, relational databases (SQL Server, Oracle, MySQL), and APIs. It supports generic ODBC drivers for broader connectivity.

Analysis of Overall Support & Compatibility Status

Sisense Fusion demonstrates strong support and compatibility, crucial for an enterprise analytics platform. The quarterly release cycle with a 12-month support window per version ensures that users have access to the latest features, security updates, and bug fixes. Broad operating system support for both server and client components, including various Windows Server and Linux distributions, caters to diverse IT infrastructures. The platform's ability to connect to numerous data sources via native connectors and generic ODBC drivers highlights its flexibility in data integration. Sisense also offers robust customer support, with teams readily available to help with issues and provide guidance.

Security Status

Sisense Fusion prioritizes security with features designed for data governance and protection.

• Security Features: Multi-level security, end-to-end governance, and the ability to define time periods for support agent access. Sisense regularly upgrades third-party libraries to address known vulnerabilities.
• Known Vulnerabilities: Sisense actively addresses vulnerabilities through updates, such as patching for Apache Log4j2 and upgrading third-party libraries.
• Blacklist Status: No information found indicating a blacklist status.
• Certifications: Not explicitly detailed in search results.
• Encryption Support: Supports secure communication via HTTPS (typically port 443) for client-server interactions and cloud deployments.
• Authentication Methods: Versatile SSO integrations are supported.
• General Recommendations: Sisense recommends keeping software updated to apply fixes for critical defects and security updates. Security Bearer Tokens, used for integrations, can have expiration dates, and users should manage them carefully, especially after upgrades.

Analysis on the Overall Security Rating

Sisense Fusion maintains a proactive approach to security, evident in its continuous updates and patching for known vulnerabilities. The platform offers multi-level security and supports versatile SSO integrations, which are essential for enterprise environments. While specific certifications are not detailed, the focus on end-to-end governance and secure communication protocols (HTTPS) indicates a commitment to data protection. Users are advised to stay current with releases and manage security tokens to ensure optimal security posture.

Performance & Benchmarks

Sisense Fusion is engineered for high performance and scalability, particularly with its In-Chip technology and Elasticube engine.

• Benchmark Scores: Not explicitly detailed in search results, but user reviews highlight strong performance.
• Real-World Performance Metrics: Users report that Sisense excels in turning complex data into clear, actionable insights, with robust data modeling capabilities and efficient handling of large datasets. The ElastiCube engine provides good performance, significantly reducing the time to build data cubes and enabling real-time analytics.
• Power Consumption: Not explicitly detailed. As a software platform, power consumption is dependent on the underlying hardware infrastructure (on-premises or cloud).
• Carbon Footprint: Not explicitly detailed. Dependent on deployment model (on-premises vs. cloud provider's efficiency).
• Comparison with Similar Assets: Sisense is often compared to other BI tools like Tableau and Power BI. It stands out for its embedded analytics capabilities, API-first approach, and ability to handle complex data. Some users find its customization options, especially for visualizations, require JavaScript knowledge, which can be a limitation compared to competitors.

Analysis of the Overall Performance Status

Sisense Fusion delivers strong performance, particularly in data processing and visualization, driven by its unique In-Chip technology and ElastiCube engine. It handles large and complex datasets efficiently, enabling real-time analytics and quick generation of insights. The platform's cloud-native architecture and elastic engine contribute to its scalability, allowing organizations to expand their analytical capabilities on demand. While direct benchmark scores are not readily available, user feedback consistently praises its speed and effectiveness in delivering actionable intelligence. Its performance makes it well-suited for embedded analytics and scenarios requiring rapid data analysis.

User Reviews & Feedback

User reviews for Sisense Fusion generally highlight its strengths in data integration, customization, and embedded analytics, while also pointing out areas for improvement.

• Strengths:
  • Data Integration and Modeling: Excels at integrating data from multiple sources, including cloud warehouses, relational databases, and APIs. Users appreciate its robust data modeling capabilities and the ability to manage data from different sources effortlessly.
  • Customizable Dashboards and Visualizations: Allows users to create interactive, customizable dashboards without heavy reliance on IT. The platform offers good visualizations and the ability to embed analytics into applications.
  • Embedded Analytics: A core strength, with extensive APIs, white-label options, and support for multi-tenancy, making it ideal for embedding analytics into products.
  • Performance: The ElastiCube engine provides good performance, reducing the time to build data cubes and enabling real-time analytics.
  • Support: Customer support is often described as exceptional, responsive, and helpful.
  • AI Features: Fusion AI generates explanations, forecasts, and what-if analyses, which users find useful and appealing.
• Weaknesses:
  • Customization Complexity: Customizing data visualizations often requires knowledge of JavaScript, which can be frustrating for users without coding expertise.
  • Setup and Learning Curve: Initial setup can be complex and may require working with the support team. The learning curve can be steep for business users unless data models are pre-curated.
  • Pricing Transparency: Pricing is not transparent and can be high, especially for cloud-hosted solutions and large enterprises, with costs varying significantly based on users, data volume, and deployment type.
  • ElastiCube Management: ElastiCube capabilities can be time-consuming and error-prone, and managing multiple query paths can add operational overhead.
  • Limited Transformation Capabilities: Live connections offer limited transformation capabilities.
  • Lack of Font Formatting: Some users dislike the lack of font formatting options.
• Recommended Use Cases:
  • Organizations looking to embed analytics into customer-facing applications or internal tools.
  • Businesses needing to combine complex data from diverse sources for real-time analysis and KPI tracking.
  • Companies with established analytics teams that can leverage advanced features and customization options.
  • Teams requiring AI-driven insights, predictive models, and automated anomaly detection.

Summary

Sisense Fusion is a powerful, AI-driven analytics platform that excels at embedding actionable intelligence into various applications and workflows. Its core strength lies in its ability to integrate diverse data sources, process complex datasets efficiently using its ElastiCube engine and In-Chip technology, and deliver highly customizable dashboards. The platform's API-first approach and robust support for embedded analytics make it a strong choice for businesses looking to differentiate their products or enhance internal decision-making with data.

Key strengths include its comprehensive data integration capabilities, flexible deployment options (cloud, on-premises, hybrid), and strong customer support. The inclusion of AI-powered features for natural language queries, forecasting, and anomaly detection further enhances its value, making advanced analytics accessible.

However, Sisense Fusion presents some challenges. Its pricing structure lacks transparency and can be a significant investment, particularly for cloud deployments and extensive user bases. The initial setup and advanced customization, especially for visualizations, may require technical expertise or JavaScript knowledge, leading to a steeper learning curve for some users. Managing ElastiCubes can also be complex and time-consuming.

Overall, Sisense Fusion is best suited for enterprises with dedicated technical resources that require a highly scalable, customizable, and embeddable analytics solution. It is particularly effective for use cases where real-time, AI-driven insights need to be seamlessly integrated into existing applications and workflows. Organizations prioritizing deep data integration and the ability to create bespoke analytical experiences will find Sisense Fusion a valuable asset, provided they are prepared for the associated costs and technical demands.

Information provided is based on publicly available data and may vary depending on specific device configurations; for up-to-date information, please consult official manufacturer resources.