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AtScale vs Tableau: What are the differences?
Data Virtualization: AtScale focuses on data virtualization, allowing users to query data without moving or copying it. This feature streamlines data access and ensures consistency across different systems. In contrast, Tableau requires data to be loaded into its software for analysis, which can lead to duplicated data and potential inconsistencies.
Aggregation: AtScale excels in handling large datasets by aggregating data at the source, ensuring fast query responses regardless of data size. On the other hand, Tableau may encounter performance issues when dealing with extensive data sets, as it processes information within its own environment.
Compatibility with Multiple Data Sources: AtScale supports a wide range of data sources and formats, enabling users to access and analyze diverse datasets seamlessly. In comparison, Tableau has limitations in data source compatibility, requiring additional tools or configurations to integrate data from different sources.
Advanced Analytics Capabilities: AtScale offers advanced analytics features such as machine learning algorithms and predictive analytics tools, empowering users to gain deeper insights into their data. Tableau, while robust in visual analytics, may lack the advanced analytical capabilities provided by AtScale.
Scalability: AtScale is designed to handle scalable workloads, making it suitable for enterprise-level data analysis with high performance and capacity. Tableau, while scalable to a certain extent, may encounter limitations in handling massive amounts of data and computations efficiently.
Governance and Security: AtScale provides robust governance and security features, allowing organizations to control access to data and ensure compliance with regulations. Compared to AtScale, Tableau may have fewer built-in governance and security functionalities, requiring additional measures to secure sensitive data effectively.
In Summary, AtScale and Tableau differ in terms of data virtualization, aggregation capabilities, data source compatibility, advanced analytics, scalability, and governance/security features.
Very easy-to-use UI. Good way to make data available inside the company for analysis.
Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.
Can be embedded into product to provide reporting functions.
Support team are helpful.
The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.
Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.
And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.
Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.
Pros of AtScale
Pros of Tableau
- Capable of visualising billions of rows6
- Intuitive and easy to learn1
- Responsive1
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Cons of AtScale
Cons of Tableau
- Very expensive for small companies2
