Looker vs Sigma Computing: What are the differences?

Introduction

Looker and Sigma Computing are both analytics platforms that enable users to analyze data, create interactive dashboards, and make data-driven decisions. However, there are several key differences between these two platforms.

1. Native vs. Web-Based Approach:

Looker is a native analytics platform that requires users to install and configure the software on their own infrastructure or cloud environment. On the other hand, Sigma Computing is a web-based platform that allows users to access and analyze data directly through a web browser without the need for any installations or configurations. This web-based approach makes Sigma Computing more accessible and user-friendly, as it eliminates the need for IT involvement and allows users to get started quickly.

2. Data Modeling Capabilities:

Looker is known for its powerful data modeling capabilities, which allow users to create and manage complex data models for analysis. It provides a robust modeling layer with features like derived tables, advanced joins, and transformations. In contrast, Sigma Computing focuses more on simplicity and ease of use, with a focus on empowering business users to perform self-service analytics without the need for extensive data modeling. While Looker is ideal for data professionals who require advanced data modeling capabilities, Sigma Computing is well-suited for business users with limited technical skills.

3. Interface and User Experience:

Looker offers a sophisticated and customizable interface with a wide range of features and options. Its interface is highly configurable, allowing users to create tailored dashboards and reports. On the other hand, Sigma Computing provides a more intuitive and user-friendly interface that requires minimal training. It focuses on simplicity and ease of use, making it an ideal choice for users who prefer a more streamlined and straightforward analytics experience.

4. Collaboration and Sharing:

Looker provides an extensive set of collaboration and sharing features, allowing users to share and collaborate on reports, dashboards, and explore data together. It offers features like commenting, sharing via links or email, and real-time collaboration. Sigma Computing also offers collaboration and sharing features, but they are more limited compared to Looker. Sigma Computing allows users to share dashboards and reports via links or embedding, but it lacks advanced collaboration features like real-time collaboration and commenting.

5. Pricing and Licensing:

Looker follows a traditional pricing model based on user licenses and data volumes. It typically requires a significant upfront investment and ongoing costs based on usage and data volumes. Sigma Computing, on the other hand, offers a modern pricing model based on usage, enabling businesses to pay only for what they need. This makes Sigma Computing more cost-effective for organizations with varying analytics needs or those looking for a more flexible and scalable pricing structure.

6. Ecosystem and Integration:

Looker has a robust ecosystem and supports a wide range of integrations with other analytics tools, databases, and data warehouses. It provides APIs, SDKs, and a marketplace for extensions and customizations. Sigma Computing, while also offering integrations with popular data sources and databases, has a more limited ecosystem compared to Looker. It primarily focuses on its core analytics capabilities, offering a streamlined and simplified solution without extensive integrations and extensions.

In Summary, Looker is a native analytics platform with advanced data modeling capabilities, extensive customization options, and a robust ecosystem. Sigma Computing, on the other hand, is a web-based platform with a focus on simplicity, accessibility, and a user-friendly interface. It offers a more intuitive analytics experience, a modern pricing model, and is a good fit for business users with limited technical skills.