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Denodo vs Tableau: What are the differences?

# Key Differences between Denodo and Tableau 

Denodo and Tableau are both widely-used tools in the field of data analytics and visualization, but they serve different purposes and have their own unique features. Below are the key differences between Denodo and Tableau:

1. **Functionality**:
Denodo is a data virtualization tool that focuses on integrating diverse data sources from various systems and providing a unified view of the data. On the other hand, Tableau is a data visualization tool that is used to create interactive and visually appealing charts, graphs, and dashboards from data stored in various sources.

2. **Data Integration**:
Denodo specializes in data integration, providing a layer of abstraction on top of multiple data sources, enabling companies to access and query data without the need to physically centralize it. Tableau, on the other hand, excels in data visualization, allowing users to create visually engaging representations of data for better decision-making.

3. **Performance**:
Denodo offers live data access, which means that users can query data in real-time from different sources. Tableau provides efficient data caching techniques, enhancing performance by storing data and improving query response times.

4. **Complexity**:
Denodo is more suited for complex data integration scenarios where data is scattered across multiple systems and requires a consolidated view. Tableau is more user-friendly and is ideal for creating simple yet powerful data visualizations and reports without the need for deep technical skills.

5. **Collaboration**:
Denodo focuses on enabling collaboration among technical teams for data integration and management. Tableau emphasizes collaboration among various business users and stakeholders for visualizing and analyzing data to make informed decisions.

6. **Deployment**:
Denodo can be deployed on-premises or in the cloud, providing flexible options based on the organization's requirements. Tableau also offers both on-premises and cloud deployment options, ensuring scalability and accessibility based on user needs.

In Summary, Denodo and Tableau serve different purposes, with Denodo excelling in data integration and providing a unified view of data sources, while Tableau specializes in data visualization and creating visually appealing dashboards for effective decision-making.
Decisions about Denodo and Tableau

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.

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Vojtech Kopal
Head of Data at Mews Systems · | 3 upvotes · 297.8K views

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.

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Pros of Denodo
Pros of Tableau
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    • 6
      Capable of visualising billions of rows
    • 1
      Intuitive and easy to learn
    • 1
      Responsive

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    Cons of Denodo
    Cons of Tableau
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      • 2
        Very expensive for small companies

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      What companies use Denodo?
      What companies use Tableau?
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        What are some alternatives to Denodo and Tableau?
        AtScale
        Its Virtual Data Warehouse delivers performance, security and agility to exceed the demands of modern-day operational analytics.
        Presto
        Distributed SQL Query Engine for Big Data
        Snowflake
        Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
        Talend
        It is an open source software integration platform helps you in effortlessly turning data into business insights. It uses native code generation that lets you run your data pipelines seamlessly across all cloud providers and get optimized performance on all platforms.
        NumPy
        Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide variety of databases.
        See all alternatives