KNIME vs Sigma Computing

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Our analysts compared KNIME vs Sigma Computing based on data from our 400+ point analysis of Business Intelligence Tools, user reviews and our own crowdsourced data from our free software selection platform.

KNIME Software Tool
Sigma Computing Software Tool

Product Basics

KNIME is an open-source end-to-end data analytics solution. It utilizes visual workflows with drag-and-drop functionality and thousands of nodes to lessen the data analytics learning curve data, with more than 1,800 prebuilt default workflows for streamlined setup.

It allows for data ingestion, preparing, cleansing, analyzing and visualizing. It can be scaled for deeper analytics through integrations with sophisticated data modeling capabilities. It can be hosted on-premise or in the cloud through Microsoft Azure.
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Sigma Computing is an analytics solution that directly connects to cloud warehouses and delivers real-time insights that drive data-informed decision making. With a spreadsheet-like interface, it provides a familiar experience for business users and analysts to utilize formulas to analyze and visualize their data. Through a self-service model, users can explore their data and ask and answer questions for themselves. It streamlines complex data analysis processes and promotes teamwork throughout a business with a balance of collaboration and control.

It is entirely cloud-based and enables data access without the risk of extracting, moving and storing data. Suitable for companies of all sizes, this SaaS runs on Windows, Mac and Linux.

Pros
  • User-friendly interface
  • Affordable pricing
  • Scalable for business growth
  • Cloud-based accessibility
  • Responsive customer support
Cons
  • Limited data analysis features
  • Less powerful than competitors
  • Occasional performance issues
  • Restricted data storage capacity
  • Lower customization options
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$0 Open-Source
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$300 Monthly
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Product Assistance

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Knowledge Base
24/7 Live Support
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Product Insights

  • Open-Source: Join a network of thousands of users, enabling collaboration and support. The source code is free to download and access.  
  • Free To Use: Save money by getting access to all of the platform’s features for free. Licensed productivity and collaboration extensions are available at a cost. 
  • Increased Business Intelligence: Get digestible, actionable data to make informed business decisions. Aggregating large datasets into predictive and prescriptive models via comprehensive visualizations and summary statistics gives users projections for the best course of action.  
  • Scalable: Obtain access to big data by scaling up the project in-platform. Integrations to distributed and multi-threaded data processing allow projects to grow. 
  • End-To-End Analytics:  It is capable of handling some tasks from start to finish without integrations. Additional integrations may be required for increasing scale and completing more sophisticated analytics. 
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  • Fast Integration: Without coding experience, users can securely and directly connect to data warehouses and get started without wasting valuable time on importing their data. Analysts can lay the foundation for the entire organization to succeed with data in hours, rather than days.
  • Ease of Use: Users work with a familiar spreadsheet-like interface and formulas to generate insights, no code required. The system automatically translates all the front-end actions input by users into SQL on the back-end.
  • Real-Time Access: Users can leverage the power of the cloud to query data directly where it lives, allowing for live analysis of massive datasets and insights in real time. 
  • Keep Data Safe: Sigma never moves, stores, copies or caches users’ data, instead running queries against the data warehouses and passing the results back to the system, ensuring that data remains secure with robust data governance and platform security that exceeds industry standards. It complies with data privacy guidelines SOC 2 Type II, CSA, GDPR and CCPA.
  • Improve Collaboration: The system eliminates BI bottlenecks and inaccurate analyses by establishing a single, reusable and accessible source of truth for all users to query. Sigma transforms the data modeling process into a collaborative one; users can edit tables and create visualizations together, enabling better communication and decision making by forging a bridge between data teams and business users.
  • Self-Service BI: Users have the freedom to explore ad hoc analysis without waiting for IT teams to update models.
  • SQL Authoring: Users with SQL technical knowledge can create and edit reusable analyses to activate with one-click parsing.
  • Free Trial or Demo: Interested customers can try out the full platform for free for 14 days, or request a demo of the solution to try with their own data warehouse.
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  • Sharing and Collaboration: KNIME Hub is an online repository for existing workflows, nodes and extensions that can be easily installed into a user’s workflow. Upload workflows and search for the components needed for projects. 
  • In-database or Distributed Processing: Process data in-database or through a distributed cluster like Apache Spark for increasing scale. It has prebuilt workflows for in-database processing, like SQL Servers. 
  • Model Predictions and Validation: Using machine learning and AI, produce predictive and prescriptive models. Use performance metrics such as AUC and R2 to verify models.  
  • Visual Workflows: Using a drag-and-drop interface, compose a workflow with little to no coding. Prebuilt generic workflows and components can be downloaded from KNIME Hub. 
  • Data Management: Handles all steps of the extract, transform and load processes. It can ingest, blend, prepare, cleanse and store structured and unstructured data. It can combine data types, including PDF, JSON, CSV and unstructured types like documents and images. 
  • Data Visualizations: Compile analyses into reports with heat graphs, bar charts, scatter plots and more. Visualizations can be exported as PDFs, PowerPoints or other formats.  
  • Tool Blending: Tools with unique domains can be combined within a workflow via native nodes. These include Python or R scripting, processing connectors, machine learning and AI. 
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  • Data Warehouse Connectivity:  Sigma connects directly with many popular data warehouses, including Snowflake, Google Big Query, Amazon Redshift and PostgreSQL, or users may pull their data from other partners like Matillion, Fivetran, Alooma and Stitch to create their central source of truth by indexing all the tables in those sources. 
  • Dataset Preparation: Sigma creates reusable datasets from individual or joined tables using one or more data sources. These Datasets can be edited either with a no-code worksheet-based interface, or with Sigma’s SQL Runner. 
  • Links: Users can add context to their Datasets by setting up the relationships between datasets in a guided, contextualized way. Non-technical users can preview and create pre-model joins without needing knowledge of the join creation process. The system also pulls pre-existing relationships in databases upon connection with a data warehouse.
  • Data Visualization: Users can create assorted kinds of charts and graphs from their worksheets, including bar charts, line graphs, pie graphs, tables and more. These visualizations can be formatted in various ways. 
  • Object Badges: Users can flag datasets and worksheets as Endorsed, Warning or Deprecated, guiding others to the most accurate and relevant data with a glance.
  • Shareable Workspaces: The platform has both individual and team workspaces, allowing for collaboration on data analysis. These workspaces can be shared externally, providing access to insights to partners or third parties who may benefit from them. The system also has an organization-wide workspace that everyone can search and explore through filters, descriptions and file names.
  • Role-Based Permissions: The system has tiered permission levels from highest to lowest for admins, authors and viewers, to allow different permissions and access settings on a role-by-role basis. Permissions may be granted on an individual or team level, allowing for organizations to add and remove users from access levels based on function, department or other categorization.
  • Data Security: In addition to role-based access control, the platform provides single-sign-on (SSO) and row-level security to ensure safe data analysis. The application has a secure infrastructure, with firewalls, credential and vulnerability checking, peer review, static code analysis, threat and anomaly detection and encryption in transit.
  • JSON Support: The visual interface enables business users to create views with JSON that unlock the value of semi-structured data. These strings of JSON can be stored, referenced and reused for analyses and visualizations across the ecosystem. 
  • Third Party Integrations: The system integrates with Slack and Google Sheets for enhanced collaboration.
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Product Ranking

#89

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#184

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User Sentiment Summary

Great User Sentiment 236 reviews
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89%
of users recommend this product

KNIME has a 'great' User Satisfaction Rating of 89% when considering 236 user reviews from 4 recognized software review sites.

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4.3 (41)
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4.6 (18)
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4.6 (139)
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3.9 (38)
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Synopsis of User Ratings and Reviews

Functionality: It provides a comprehensive set of nodes and functions to process large quantities of data, as noted by 69% of users who referred to functionality.
User Friendly: It is intuitive and easy to use, as noted by 79% of reviewers who refer to ease of use.
Connectivity: Around 77% of users who talked about connectivity mentioned its ability to seamlessly connect and integrate with multiple sources.
Cost: All users were happy that the solution is available free of charge, with no data limits.
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User-friendly interface: Sigma's intuitive design and drag-and-drop functionality make it easy for users with limited technical expertise to get started and create insightful reports.
Affordable pricing: Sigma offers a competitive pricing model with a free tier for individual users and small teams, making it accessible to businesses of all sizes.
Scalable for business growth: Sigma's cloud-based architecture scales seamlessly to accommodate growing data volumes and user bases, ensuring your BI solution can grow with your business.
Cloud-based accessibility: Access your data and insights from anywhere, anytime with Sigma's cloud-based platform, eliminating the need for on-premise infrastructure.
Responsive customer support: Sigma provides responsive and helpful customer support via email, phone, and live chat, ensuring you get the assistance you need when you need it.
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Performance: Nearly 95% of reviewers who mentioned performance said that the solution runs slowly and uses too much CPU and memory.
Visualization: Approximately 67% of users who specified visualization talked about its lack of proper visualization options.
Support: About 67% of users who reviewed support mentioned how hard it is to get proper documentation or support.
Learning Curve: KNIME has a steep learning curve, according to about 64% of users who mentioned the learning curve.
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Limited data analysis features: Compared to more robust BI solutions, Sigma offers a less extensive range of advanced data analysis capabilities.
Occasional performance issues: Some users have reported encountering occasional performance issues, such as slow loading times and data refreshes.
Restricted data storage capacity: Sigma's free and lower-tier plans offer limited data storage, requiring upgrades for larger datasets.
Lower customization options: While Sigma offers some customization options, its capabilities are not as extensive as other BI platforms.
Less powerful than competitors: Although Sigma excels in user-friendliness, it may lack the power and flexibility required for complex data analysis needs.
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KNIME is a robust open-source solution with cross-platform interoperability. It integrates with a range of software, such as JS, R, Python and Spark. With a variety of nodes and functions, it can process large datasets with a decent level of control in each step. Workflows are displayed as connected nodes, making it easy to isolate and fix specific steps. It also contains built-in tools to create and test supervised and unsupervised machine learning models. Users found the UI very intuitive and flexible. On the flip side, they found the tool visually lacking and primitive. The system also has performance and stability issues. Processing big data is very time consuming since the platform isn’t cloud-based. Users reported excessive memory usage as well. It also lacks reporting or monitoring features. Decent technical knowledge is required to fully leverage its capabilities.

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While Sigma Computing receives praise for its user-friendly interface and affordability, some users feel it lacks compared to similar BI tools like Tableau and Power BI. One user noted, "Sigma is great for beginners, but I quickly outgrew its capabilities. It just doesn't offer the depth of analysis I need." Another echoed this sentiment, stating, "The lack of advanced features was a dealbreaker for me. While Sigma is easy to use, it's not powerful enough for complex data analysis." However, others find Sigma's strengths outweigh its weaknesses. One user commented, "For the price, Sigma is a fantastic tool. It's simple to use and allows me to create insightful reports quickly and easily. I don't need all the bells and whistles offered by other platforms." Another user praised its scalability, saying, "Sigma has grown with my business. As my data volume increased, Sigma seamlessly scaled to accommodate my needs." One differentiating factor is Sigma's focus on real-time data and collaboration. One user highlighted this, saying, "Sigma's ability to work with real-time data is a game-changer. It allows me to make decisions based on the latest information, not outdated data." Another user noted the benefits of collaboration, stating, "Sigma's collaborative features make it easy to work with my team on data analysis. We can share insights and brainstorm ideas in real-time." Ultimately, the suitability of Sigma Computing depends on individual needs and priorities. If you're a small business or individual user who needs a basic, affordable BI tool, Sigma is a great option. However, if you require advanced data analysis capabilities or extensive customization options, you may be better served by a more powerful BI platform.

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