Qrvey vs Tableau

See why Qrvey is the best choice for distributed and embedded analytics use cases.

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What Makes Us Different

Qrvey simplifies business analytics by leveraging the power of Amazon Web Services (AWS) to solve the three biggest problems of traditional analytics tools. 

Up to 70% of all business data cannot be analyzed by traditional analytics because they only work with structured data. They also lack a modern architecture that can deliver the performance needed for today’s demanding analytics projects. And finally, traditional analytics have long suffered poor user adoption, failing to get critical insights into the hands of those who need them the most. 

Tableau is among those legacy analytics tools that Qrvey was designed to replace. It is limited in the types of data it can analyze, it cannot deliver best-in-class performance and, as a desktop application, it suffers from the user adoption problem.

Key Differentiators 
for Software Companies

One

All Data Accepted

Tableau is compatible with all ODBC-compliant data sources and performs best with small to midsize data volumes. Qrvey is able to analyze structured, semi- and unstructured datasets as well as ingest, transform and aggregate all data into Elasticsearch for maximum performance even with large datasets spanning hundreds of millions of rows. Since Qrvey is deployed into existing AWS cloud accounts, data security and privacy are ensured.

Two

Architecture

Tableau uses a traditional client/server architecture that heavily relies on its desktop application. The server component can be run inside a container “in the cloud” but does not run cloud-native. Qrvey is 100% cloud-native and leverages microservices for maximum flexibility and scalability. As a cloud-native platform, Qrvey uses 26 different AWS microservices, including several AI and ML services. Tableau relies on third-party integrations and connections to provide advanced functionality, such as machine learning.

Three

All-in-One Platform

Qrvey is an all-in-one platform that includes data collection, transformation, analysis, automation and actions. Tableau uses third-party integrations with companies like Alteryx for data ingestion and ETL while offering no built-in automation capabilities beyond basic scheduling and alerts.

Four

Self Service & Embedded

The Qrvey platform includes APIs and pre-built widgets for white-labeling and embedded use cases. Tableau remains largely a single-user desktop tool with some sharing and limited embedding capabilities.

Five

Licensing

Tableau has traditional user-based licensing. Qrvey encourages increased user adoption with unlimited licensing that can be used as a stand-alone product for individuals and teams, as an embedded or white-labeled analytics platform for software companies or deployed as servware by service providers and systems’ integrators.

Tableau vs. Qrvey Comparison

 TableauQrvey
ArchitectureDesktop designer and a traditional web server Cloud-native microservices deployed to your AWS
Data SourcesPrimarily ODBC-compliant databases and similar flat data sources All data accepted including unstructured, semi-structured, nested, hierarchical and databases
Use CasesVisual analysis, data science exploration All-in-one platform for custom analytics, self-service dashboards and embedded data automation
Data Collection /
ETL Capabilities
Partner solutions required for data extraction, transformation and loading Built-in data collection, transformation and loading capabilities in our all-in-one platform
Performance and ScaleTraditional client-server and web server scalability meant for smaller-scale data volumes and user activities Fully Elastic and cloud-scale that works with multi-TB data sources with sub-second response times and auto-scales to any number of users
DashboardsRich set of charts, metrics, and data visuals Fully embeddable and actionable charts, metrics, and visuals
Mobile / Responsive
Limited support for mobile and tablet interfaces Designed to be 100% responsive with outputs running automatically on mobile and touch devices
Embedding & White LabelLimited support for embedding without white labeling Fully embeddable with full support for white-labeling
AWS CloudRuns inside of a container on AWS 100% AWS cloud-native with microservices, deployed into your AWS account
AI & ML3rd party AI and ML tools available Platform includes AWS AI and ML services directly with no coding required
Automation and WorkflowLimited to basic alerts and schedules Full self-service data-driven automation with conditional logic, actions and notifications that can be embedded or stand-alone
License ModelTraditional, user-based licensing Unlimited users to encourage user adoption with licensing based on data size. Perfect for embedded uses cases

Tableau vs. Qrvey

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