Sold by: Sisense
Deployed on AWS
Sisense Fusion Analytics Platform offers AI-powered analytics for AI-driven data products, delivering insights to outperform competitors.
4.2
Overview
Sisense is an API-first analytics platform that modernizes businesses by seamlessly integrating in-context analytics within applications, leading to action-oriented insights that enhance decision intelligence. For custom orders through private offers, proof of concepts, or custom trial terms, please reach out to your dedicated Sisense representative or email us at awssales@sisense.com
Highlights
- Differentiate your products, create new revenue streams and increase stickiness with embedded AI-powered analytics for your customers.
Details
Sold by
Delivery method
Deployed on AWS
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Buyer guide
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Financing for AWS Marketplace purchases
AWS Marketplace now accepts line of credit payments through the PNC Vendor Finance program. This program is available to select AWS customers in the US, excluding NV, NC, ND, TN, & VT.
Pricing
Custom pricing options
Pricing is based on your specific requirements and eligibility. Request a private offer to receive a custom quote. Sign in to view any offers that have been extended to you.
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Delivery details
Software as a Service (SaaS)
SaaS delivers cloud-based software applications directly to customers over the internet. You can access these applications through a subscription model. You will pay recurring monthly usage fees through your AWS bill, while AWS handles deployment and infrastructure management, ensuring scalability, reliability, and seamless integration with other AWS services.
Resources
Vendor resources
Support
Vendor support
Customer Success Manager: Each client is assigned a main focal point to business planning, training and other related questions. Support: Questions or assistance required after onboarding are submitted through our central ticketing systems. Online Training is available on-demand. Sisense Community: Managed forums provide clients a community to pose a question
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By ThoughtSpot
By Omni Analytics
Top
10
In Analytic Platforms, Data Analytics, Business Intelligence & Advanced Analytics
Top
10
In Analytics, Data Warehouses
Top
25
In Data Governance, Business Intelligence & Advanced Analytics
Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
API-First Architecture
Platform designed with API-first approach enabling seamless integration of analytics capabilities within applications
Embedded Analytics
Capability to embed in-context analytics directly within applications for action-oriented insights
AI-Powered Analytics
Analytics engine powered by artificial intelligence for generating insights and data-driven recommendations
Data Integration
Seamless integration of analytics across business systems and applications for unified data analysis
Decision Intelligence
Analytics platform designed to enhance decision-making capabilities through integrated insights and analytics
Agentic AI Analysis
Spotter agentic AI analyst answers plain-language questions with multi-step reasoning and conversational interface for self-service analytics at scale.
Automated Visualization Creation
SpotterViz generates complete, story-driven Liveboards from a single prompt with real-time, interactive data views.
Multi-Cloud Data Warehouse Compatibility
Runs live against cloud data warehouses including Amazon Redshift, Snowflake, Databricks, Google BigQuery, and Azure Synapse.
Row-Level Data Governance
Enterprise-grade security and row-level governance controls maintained across all analytics operations and self-service access.
Semantic Layer Architecture
Built-in semantic model that provides governed metrics and ensures consistency across analytics queries and AI-generated answers
Conversational AI Analytics
Natural language processing capability enabling users to ask AI questions and receive trusted answers without requiring SQL knowledge
Git Integration and Version Control
Git-based integration with branching, content validation, and version history for managing changes to semantic models and analytics content
Excel Workflow Integration
Native Excel spreadsheet compatibility allowing users to perform financial modeling, forecasting, and exploratory analysis within the platform
Software Development Lifecycle Features
CICD pipeline support, content validation, and developer workflows for safely testing and deploying model changes across environments
Standard contract
No
Customer reviews
Wicklife Womon
Self-service dashboards have streamlined data analysis and improved decision-making
Reviewed on Oct 12, 2026
Review from a verified AWS customer
What is our primary use case?
I use Sisense in my day-to-day work because it displays all the information I need in one place, and I can seamlessly use it within my platform.
It is a great tool that allows me to connect directly to different data sources and transform the data. I can easily compare information from various sources. I also appreciate that I can ask questions directly to my data for deeper analysis. Building dashboards with no code is a significant advantage for me, and I value how more technical users can customize views with scripts and more detailed coding, especially using the Compose SDK. The Compose SDK is extremely valuable for self-service BI, as it allows me to customize everything and render views and widgets directly on my front end.
Connecting with our data warehouse and other sources was very straightforward, and creating dashboards was simple after data modeling in the ElastiCubes.
How has it helped my organization?
Sisense has positively impacted my organization by serving as an excellent tool for displaying complex data analysis in our platform. I appreciate the drag-and-drop feature, which helps me create dashboards that range from very simple to complex and allows me to focus on data more than coding.
I also value the customizability, which has enabled me to use SQL to model the data and tailor the dashboard user interface. I value it because it supports various widget types, making it easy to theme dashboards and display data intuitively.
What is most valuable?
In my opinion, the best features Sisense offers include customizability, which is a major advantage for me, especially being able to use SQL to model the data and tailor the dashboard interface.
I also value the drag-and-drop feature for creating dashboards, which can range from very simple to very complex, allowing me to focus on data rather than coding.
I find the available integrations valuable in Sisense because they make data ingestion straightforward, and I also view it as very flexible.
What needs improvement?
My experience with Sisense has been very positive. However, one area that really needs improvement is the cost to fit even smaller organizations working with tight budgets.
I would add that they should improve the management of cubes in Sisense because it is cumbersome and requires high system resources.
For how long have I used the solution?
I have been using Sisense for the past three years.
What was our ROI?
I can share specific outcomes and metrics showing how Sisense has made a difference for my organization. Some of the return on investment that we have greatly experienced from Sisense is that automated reporting has reduced manual data processing, allowing our team to focus on core tasks and saving us time and money.
Implementation and training required an upfront investment in time and resources. However, handling very large datasets has made performance slow and hence impacted efficiency temporarily, which represents a negative return on investment.
What other advice do I have?
I chose a rating of nine out of ten because Sisense is a very intuitive platform with a user-friendly and intuitive UI with minimal learning curve, even for non-technical users.
Regarding Sisense's AI capabilities, I feel my data is well-protected from what I have been using and observing. There are clear controls on who can access and modify sensitive information.
Regarding the AI capabilities, I believe the accuracy and reliability of the output is quite good.
I purchased Sisense through the AWS Marketplace.
The advice I would give to others considering Sisense is that it is an excellent platform for data modeling through ElastiCubes. It is easy to visualize the joins between objects, preview data, and identify data types. It is also very easy to use, even for non-technical users, making it a highly recommendable platform for everyone. My overall rating for Sisense is nine out of ten.
Financial Services
Elasticube and Integrations Shine, with Flexible Embedded Analytics via Compose SDK
Reviewed on Oct 09, 2026
Review provided by G2
What do you like best about the product?
The ability to easily store and manage data in the Elasticube is one of Sisense's strongest features. The available integrations make data ingestion straightforward, and the Compose SDK provides a flexible and modern way to embed analytics into products. The support team has also been consistently responsive and helpful, making it easier to resolve issues and accelerate development.
What do you dislike about the product?
The UI experience could be improved, particularly when dashboards are embedded into products using iFrames, where performance can sometimes be less than optimal. While the AI capabilities show promise, the platform would benefit from broader support for AI models and deeper integrations with additional model providers to offer more flexibility and choice. Pricing should be kept optimal especially for self hosting customers.
What problems is the product solving and how is that benefiting you?
Sisense helps us rapidly develop and embed analytics experiences without having to build the entire data and visualization stack from scratch. By using the Elasticube as a centralized data backbone and the Compose SDK for embedding analytics, we can quickly create charts, dashboards, and AI-powered experiences within our products. This has significantly accelerated development, saving our team several weeks of effort while allowing us to focus on delivering business value rather than building and maintaining analytics infrastructure.
Xin H.
Easy Embedding for Basic Dashboards, but Hard to Customize Without JavaScript
Reviewed on Oct 02, 2026
Review provided by G2
What do you like best about the product?
Easy to get embedded and meets basic dashboard needs
What do you dislike about the product?
It’s not very designer-friendly for anyone who doesn’t use JavaScript (or similar tools). I find it very difficult to manipulate the dashboards.
What problems is the product solving and how is that benefiting you?
Publish dashboards inside web app and share to users
Computer Software
Easy Dashboard Build and Deployment, but Limited Visualisation Options
Reviewed on Sep 29, 2026
Review provided by G2
What do you like best about the product?
It’s relatively easy and straightforward to build, test, and deploy dashboards that are both helpful and informative.
What do you dislike about the product?
There aren’t many data visualisation options available, and more advanced functionality often requires using scripts to make full use of it.
What problems is the product solving and how is that benefiting you?
Deploying analytics and data to a large number of customers across many databases.
Brad Dyke
Embedded analytics has streamlined customer insights while data scaling remains a key improvement
Reviewed on Sep 23, 2026
Review from a verified AWS customer
What is our primary use case?
My main use case for Sisense during our three-year period involved a review, an implementation, and then a progression upgrade.
A specific example of how I used Sisense during that time is that we principalized it for the SaaS front-end platform, diversifying analytic dashboarding for our customer base and allowing them to use the relationships of the review products versus the actual outcome of the people who reviewed it and the analytics that supported that.
The key thing I want to add about how Sisense fits into our workflow is that we wanted to ensure the SDK packaging was flexible, which it is, and it has a solid API and SDK option package that we can work with for compatibility for our SaaS services, while also meeting our manpower requirements to drive costs down.
How has it helped my organization?
Reduced needs for additional hires was the biggest key component; we almost had zero cost spin-up outside the initial cost of the product package itself, and it was the overhead of manpower that mattered to us. Basically, to control costs, as we could not hire many extra resources, and the sustainment overhead was very low, allowing us to focus primarily on productivity rather than operational overhead.
What is most valuable?
The best features Sisense offers include ease of use and the ability to associate the API integration down to the dashboard, which made it a little less overhead for us to scale the product into our existing SaaS platform, along with the availability of professional services that helped to get our development off the ground.
The standout factors regarding the API integration and dashboarding for my team are that it can take standardized APIs that we have with JSON and other platforms, and it supports our writing of custom APIs, translating fairly well to the dashboarding process.
What needs improvement?
Areas where Sisense can be improved include AI integration, particularly effective deployment of the AI tool, rather than just having AI, and addressing the challenges around infra-scaling to support multi-cloud models instead of just a single cloud provider.
The needed improvements around scaling and AI integration include addressing the scaling functionality, particularly in disaster recovery, and enabling more effective synchronization or asynchronous functionalities with the DR services.
For how long have I used the solution?
I have been using Sisense for three years.
What do I think about the stability of the solution?
Sisense has been stable so far.
What do I think about the scalability of the solution?
Sisense's scalability is tricky; I would like to see more infra-scaling functionality for effective injection capacity and DR functionality.
How are customer service and support?
I find customer support for Sisense to be good.
I would rate customer support an eight on a scale of one to ten.
Which solution did I use previously and why did I switch?
I did not previously use a different solution before Sisense; this was a new attempt.
How was the initial setup?
Integrating Sisense with my existing data sources and applications was not difficult; I would rate it about an eight or eight point five on a scale of one to ten.
What about the implementation team?
The improvements I have mentioned are significant and pretty detailed.
What was our ROI?
I have not seen a return on investment in terms of employee numbers, but it has introduced a new potential source of revenue as a product we could integrate with our analytics tools for our customer base.
What's my experience with pricing, setup cost, and licensing?
Regarding pricing, setup cost, and licensing, the version six point three point one release was good initially, but I had to keep a close eye on costs, as it requires maintaining a tight format to avoid runaway costs.
Which other solutions did I evaluate?
I evaluated other options, although I was not present during those reviews, so I cannot specify the vendors.
What other advice do I have?
My advice for others looking into using Sisense is to ensure it fits your SDK guidelines, API guidelines, and is suitable for your customer-oriented goals rather than internal use. I would rate this review a seven overall.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)