The Difference is Clear
The Sisense platform is now showing its age. Their server-based architecture limits both their capabilities and their ability to scale to meet today’s data needs. They are also not truly cloud-native (although they claim to be) and their data model does not support semi- or unstructured data. While Sisense has seen some success in embedded applications, its licensing and business model has never fully supported embedded and distributed use cases.
|No Code Required|
|Fully Elastic / Auto Scaling|
|Dashboards and Visualizations|
|100% Mobile / Responsive|
|Fully Embeddable / White Label|
|AI & ML|
|Natural Query Language|
|Automation & Workflows|
5 Key Ways Qrvey Beats Sisense
Uses Outdated Architecture
Sisense consists of two components: a frontend web-based UI and a proprietary backend data store called ElastiCube. Both components can be clustered to support scalability but both rely on legacy Windows servers to manage deployments and are not native cloud applications.
Qrvey is 100% Cloud-Native
Qrvey is a native cloud-based platform that is deployed into your existing cloud account on AWS. This ensures that you’re always in control of your data and infrastructure and can quickly and cost-effectively scale up or down as needed using Qrvey’s compilation of dozens of different AWS microservices.
2. Data Performance
Performance is Connector-Dependent
The Sisense ElastiCube supports the SQL92 standard and can be connected out of the box to many common SQL and structured data sources. ElasticCube supports live connections to certain data sets, while others must be refreshed at regularly scheduled intervals. Sisense will not process data at the speed of your business.
Qrvey Scales Automatically
Qrvey is built on Elasticsearch and provides industry-leading performance, scalability and flexibility to meet even the most demanding use cases. Additionally, Elasticsearch allows Qrvey to work with all your data, including semi- and unstructured data, eliminating the dark data problem.
Focused on Data Visualizations
Sisense is a traditional BI platform that offers tools to build data visualizations such as charts, reports, metrics and dashboards. Sisense also includes its ElastiCube data storage technology, but it lacks data collection, automation and enhanced AI/ML capabilities to add analytics to your entire data pipeline.
Qrvey is an All-in-One Platform
Qrvey is an all-in-one analytics platform that includes data collection, transformation, analysis, automation and actions as well as integration with AI/ML capabilities. It allows users to build robust analytics applications and complete data pipelines for individual, self-service and embedded use cases.
4. AI/ML Capabilities
AI/ML is not Pervasive
Sisense includes AI-enabled forecasting and in April 2020 the company added natural language query (NLQ) functionality to its platform, however, AI/ML functionality is still not pervasive throughout its offerings.
AI/ML Incorporated Throughout
AWS has been at the forefront of AI/ML and Qrvey has been leveraging those capabilities throughout its platform. New data is automatically profiled to provide text recognition, object detection, keyphrases and sentiment analysis. Qrvey integrates with AWS Sagemaker for advanced user-defined ML modeling.
Licensing Is Not Scaleable
Sisense offers embedding for certain B2B use cases, however it is typically licensed on a per-user basis, factoring in the number of data sources it’s connected to, among other variables. This makes it less than ideal for embedded applications that require large and dynamic user bases.
Qrvey Includes Unlimited Users
Qrvey was built from the ground up with a B2B mindset. It includes robust APIs and pre-built UI widgets for white-labeling and embedded use cases. And Qrvey is packaged and licensed for embedded use cases with the experience, support and guidance you need to be successful.