Top Alteryx Alternatives & Competitors For 2024

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Looking for alternatives to Alteryx? Many users crave user-friendly and feature-rich solutions for tasks like Dashboarding and Data Visualization, Data Management, and Machine Learning. Leveraging crowdsourced data from over 1,000 real Big Data Analytics Tools selection projects based on 400+ capabilities, we present a comparison of Alteryx to leading industry alternatives like WebFOCUS, BigQuery, SAS Viya, and Hadoop.

WebFOCUS Software Tool
Hadoop Software Tool

Product Basics

The Alteryx platform is a suite of five products offering self-service statistical, predictive and spatial data analytics to achieve enterprise, financial and industrial intelligence. It allows users to create repeatable extract-transform-load workflows, with or without a programming language. Its scalable performance and deployment options enable analysis from the enterprise to big data levels.

A drag-and-drop interface enables high-speed analytics and modeling, supported by a community of model developers in the vendor’s customer base. Depending on the products selected from the suite, it can perform end-to-end BI, from data harvesting from deep data pools to automated operationalizing.
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WebFOCUS is a comprehensive data management and analytics platform that enables organizations to access, transform, visualize, and distribute data across multiple platforms. It's particularly well-suited for enterprises with large, complex datasets and a need for robust reporting and analytics capabilities. Key benefits include its ability to unify disparate data sources, create interactive dashboards and visualizations, and automate data-driven workflows. Popular features include its drag-and-drop report builder, self-service data exploration tools, and integration with various business intelligence applications. User experiences generally praise its ease of use, scalability, and ability to handle diverse data types. Pricing is typically based on the number of users, data sources, and required features, with options for both on-premise and cloud-based deployments.

Pros
  • Easy to use interface
  • Handles large datasets
  • Diverse data source integration
  • Customizable reports and dashboards
  • Scalable for enterprise needs
Cons
  • Occasional performance issues
  • Limited out-of-the-box visualizations
  • Upgrades can be complex
  • UI may feel outdated to some
  • Learning curve for advanced features
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BigQuery, a cloud-based data warehouse offered by Google, provides businesses with a scalable and cost-effective solution for analyzing massive datasets. It eliminates the need for infrastructure management, allowing users to focus on extracting valuable insights from their data using familiar SQL and built-in machine learning capabilities. BigQuery's serverless architecture enables efficient scaling, allowing you to query terabytes of data in seconds and petabytes in minutes.

BigQuery is particularly well-suited for organizations dealing with large and complex datasets that require rapid analysis. Its ability to integrate data from various sources, including Google Cloud Platform and other cloud providers, makes it a versatile tool for businesses with diverse data landscapes. Key benefits include scalability, ease of use, and cost-effectiveness. BigQuery offers a pay-as-you-go pricing model, allowing you to only pay for the resources you consume. You are billed based on the amount of data processed by your queries and the amount of data stored.

While BigQuery offers numerous advantages, it's important to consider factors such as your specific data analytics needs and budget when comparing it to similar products. User experiences with BigQuery have generally been positive, highlighting its speed, scalability, and ease of use. However, some users have noted that the pricing structure can become complex for highly demanding workloads.

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SAS Viya is a cloud-based in-memory analytics engine that provides data visualization, reporting and analytics to businesses for actionable data insights. Powered by AI, it brings together visual analytics, visual statistics and data science for enterprises to achieve end-to-end self-service analytics. It uses a standardized code base with support for programming in R, Python, SAS, Java and Lua.

Deployable in the cloud, on-premises and hybrid environments, it integrates with a wide range of business applications through an agile, scalable architecture. The vendor offers an introductory 30-day free trial.

Pros
  • Comprehensive features
  • Powerful analytics capabilities
  • User-friendly interface
  • Scalable architecture
  • Strong support from SAS
Cons
  • Steep learning curve
  • Limited customization options
  • High cost of ownership
  • Potential vendor lock-in
  • Resource-intensive
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Apache Hadoop is an open source framework for dealing with large quantities of data. It’s considered a landmark group of products in the business intelligence and data analytics space, and is comprised of several different components. It functions on basic analytics principles like distributed computing, large data processing, machine learning and more.

Hadoop is part of a growing family of free, open source software (FOSS) projects from the Apache Foundation, and works well in conjunction with other third-party products.
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Product Assistance

Documentation
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24/7 Live Support
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Product Ranking

#8

among all
Big Data Analytics Tools

#50

among all
Big Data Analytics Tools

#10

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Big Data Analytics Tools

#41

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#1

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Big Data Analytics Tools

Find out who the leaders are

Analyst Rating Summary

86
we're gathering data
we're gathering data
94
we're gathering data
69
we're gathering data
we're gathering data
96
we're gathering data
54
we're gathering data
we're gathering data
100
we're gathering data
89
we're gathering data
we're gathering data
98
we're gathering data
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Data Management
Integrations and Extensibility
Availability and Scalability
Geospatial Visualizations and Analysis
Machine Learning
Availability and Scalability
Computer Vision and Internet of Things (IoT)
Dashboarding and Data Visualization
Data Management
Geospatial Visualizations and Analysis
Availability and Scalability
Computer Vision and Internet of Things (IoT)
Dashboarding and Data Visualization
Data Management
Geospatial Visualizations and Analysis
Availability and Scalability
Computer Vision and Internet of Things (IoT)
Platform Security
Dashboarding and Data Visualization
Augmented Analytics
Availability and Scalability
Computer Vision and Internet of Things (IoT)
Dashboarding and Data Visualization
Data Management
Geospatial Visualizations and Analysis

Analyst Ratings for Functional Requirements Customize This Data Customize This Data

Alteryx
WebFOCUS
BigQuery
SAS Viya
Hadoop
+ Add Product + Add Product
Augmented Analytics Computer Vision and Internet of Things (IoT) Dashboarding and Data Visualization Data Management Data Preparation Geospatial Visualizations and Analysis Machine Learning Mobile Capabilities Platform Capabilities Reporting 69 54 89 100 96 93 0 86 96 100 98 96 86 93 70 96 0 25 50 75 100
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Analyst Ratings for Technical Requirements Customize This Data Customize This Data

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User Sentiment Summary

Excellent User Sentiment 496 reviews
Great User Sentiment 439 reviews
Excellent User Sentiment 724 reviews
Great User Sentiment 203 reviews
Great User Sentiment 474 reviews
90%
of users recommend this product

Alteryx has a 'excellent' User Satisfaction Rating of 90% when considering 496 user reviews from 4 recognized software review sites.

87%
of users recommend this product

WebFOCUS has a 'great' User Satisfaction Rating of 87% when considering 439 user reviews from 5 recognized software review sites.

90%
of users recommend this product

BigQuery has a 'excellent' User Satisfaction Rating of 90% when considering 724 user reviews from 3 recognized software review sites.

85%
of users recommend this product

SAS Viya has a 'great' User Satisfaction Rating of 85% when considering 203 user reviews from 3 recognized software review sites.

85%
of users recommend this product

Hadoop has a 'great' User Satisfaction Rating of 85% when considering 474 user reviews from 3 recognized software review sites.

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4.5 (14)
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4.5 (158)
4.4 (158)
4.4 (292)
4.2 (157)
4.3 (101)
4.7 (74)
4.5 (170)
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4.3 (33)
4.3 (244)
4.4 (56)
4.3 (65)
4.6 (283)
4.7 (13)
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4.5 (208)
3.2 (32)
4.4 (149)
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4.2 (129)

Awards

User Favorite Award
Integrations and Extensibility Award
we're gathering data
User Favorite Award
Analysts' Pick Award
Augmented Analytics Award
Computer Vision and Internet of Things (IoT) Award
we're gathering data

Synopsis of User Ratings and Reviews

Data Analysis: All users who reviewed analytics said that the platform adds value to data through features such as statistical modeling and predictive analysis.
Data Processing: Around 86% of the users who mentioned data processing said that, with a lightweight ETL tool, the solution excels at data wrangling for further analysis.
Data Integration: Citing strong integration with multiple data sources and tools, around 84% of the users said that it works well with big data.
Ease of Use: Approximately 83% of the users who mentioned ease of use said that the platform’s low-code approach, with drag-and-drop functionality, makes the interface user-friendly.
Online Community: The online community is responsive and helpful, according to around 74% of users who discussed support for the platform.
Functionality: With fuzzy matching and join capabilities, the platform is feature-rich and versatile, said approximately 63% of users who discussed functionality.
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Support: All of the users who mentioned the vendor’s support praised their responsive, helpful support team and dedication to customer success.
Reporting: Around 96% of users who mentioned reporting said that this tool works well for report creation and scheduled distribution.
Data Visualization: About 90% of users who reviewed the tool for data visualization said that it excels in dashboard and chart creation.
Functionality: This is a robust, feature-rich tool with a great degree of flexibility and frequent updates, according to around 76% of users who reviewed the tool’s functionality.
Ease of Use: According to about 63% of users who reviewed the platform’s ease of use, its intuitive drop-and-drop interface simplifies data analysis and visualization.
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Performance: The system can execute queries on massive amounts of data with agility, as specified by about 89% of users who mentioned performance.
Functionality: About 68% of users who reviewed functionality talked about its robust inbuilt features.
Ease of Use: The UI is simple and easy to navigate, according to about 72% of users who talked about user-friendliness.
Integration: Approximately 75% of reviewers who talked about integration said that it connects to numerous other tools seamlessly.
Scalability: All users who reviewed scalability said that the platform scales to thousands of servers.
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Ease of Use: All users who mention its interface say that it makes autonomous analysis and data modeling accessible to users of all skill levels.
Support: All users who review support say that representatives are responsive and helpful in resolving issues and queries.
Functionality: Around 71% of the users who comment on its feature set say that the software helps discover data insights through powerful visualizations and on-the-fly calculations.
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Scalability: Hadoop can store and process massive datasets across clusters of commodity hardware, allowing businesses to scale their data infrastructure as needed without significant upfront investments.
Cost-Effectiveness: By leveraging open-source software and affordable hardware, Hadoop provides a cost-effective solution for managing large datasets compared to traditional enterprise data warehouse systems.
Flexibility: Hadoop's ability to handle various data formats, including structured, semi-structured, and unstructured data, makes it suitable for diverse data analytics tasks.
Resilience: Hadoop's distributed architecture ensures fault tolerance. Data is replicated across multiple nodes, preventing data loss in case of hardware failures.
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Cost: In addition to the high cost of licenses, the price of add-ons is limiting, said around 89% of the users who reviewed pricing.
Data Visualization: Around 75% of users who reviewed its presentation capabilities said that with outdated graphics, the platform lags behind other solutions in data visualization.
Performance: The solution is prone to infrequent crashes, especially when processing large amounts of data, as said by 65% of users who discussed performance.
Training: Approximately 54% of the users who reviewed learning said that with the documentation not being up to date with latest features, there is a steep learning curve and training is required.
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User Interface: Of the users who mentioned this solution’s UI, approximately 87% said that it looks outdated, especially compared to those of competitors.
Cost: About 83% of users who reviewed it for price said that this solution is expensive, especially when considering add-on modules.
Performance: All of the users who reviewed the platform’s performance and speed mentioned bugs, lag and crashes, among other issues.
Learning Curve: It takes some time to learn this platform, according to about 60% of users who reviewed its learning curve.
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Cost: Approximately 76% of users who mentioned cost complained that it’s expensive, and charges can rack up quickly if queries aren’t properly constructed.
Learning Curve: About 82% of users mentioned that the software has a steep learning curve.
Resources: About 89% of users who spoke about resources said that documentation and video tutorials are lacking and need improvement.
Visualization: Data visualization capabilities aren’t up to the mark, according to all users who talked about visualization.
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Cost: All users who discuss its pricing say that the cost of acquisition is high.
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Complexity: Hadoop can be challenging to set up and manage, especially for organizations without a dedicated team of experts. Its ecosystem involves numerous components, each requiring configuration and integration.
Security Concerns: Hadoop's native security features are limited, often necessitating additional tools and protocols to ensure data protection and compliance with regulations.
Performance Bottlenecks: While Hadoop excels at handling large datasets, it may not be the best choice for real-time or low-latency applications due to its batch-oriented architecture.
Cost Considerations: Implementing and maintaining a Hadoop infrastructure can be expensive, particularly for smaller organizations or those with limited IT budgets.
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Alteryx is a data science solution that leverages the power of AI and ML to blend, parse, transform and visualize big business data to promote self-serve analysis of business metrics. Many users who reviewed data analysis said that the tool performs statistical, spatial and predictive analysis in the same workflow. Most of the users who reviewed data processing said that, with a lightweight ETL tool, the platform has strong data manipulation and modeling efficiencies, though some users said that it can be tricky to use SQL queries. Citing integration with Power BI, Tableau and Python, most of the users said that the tool connects seamlessly to data from databases and files, apps, and third-party data sources, among others, to expand the reach of search-based and AI-driven analytics. Most of the users who discussed ease of use said that the tool is intuitive with drag-and-drop functionality and a well-designed interface, though some users said error handling can be challenging for automated workflows. Most of the users who reviewed support said that online communities are helpful in providing answers to queries. Citing automated workflows, many users said that the tool helps save time, though some users said that these can be overly complex and need improvement. On the flip side, many users who reviewed pricing said that its expensive licenses and add-ons are cost-prohibitive, and cost per core is high for enterprises looking to scale. A majority of users who reviewed its visualization capabilities said that they need to export data to visually stronger applications, such as Tableau or Power BI, to make the reports presentation-worthy. Citing slow runtimes when executing complex workflows, especially with large datasets, many users said that performance-wise, the solution is prone to infrequent crashes. Most of the users who discussed learning said that with documentation not being in sync with latest releases, training is a must to optimally use the tool. Overall, Alteryx is a data science tool that, with its low-code approach and strong data wrangling capabilities, makes the journey from data acquisition to data insights seamless and promotes data literacy across organizations, though it might be better suited for medium- to large-sized organizations.

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WebFOCUS offers a feature-rich business intelligence data and analytics platform that unlocks actionable insights and the power of decision-making for users throughout an organization. Rated highly for ease of use by most reviewers, it empowers self-service data discovery with a user-friendly UI that enables drag-and-drop data analysis and visualization; some users noted that this UI looks outdated, especially compared to those of competitors. The platform offers a wide range of prebuilt data visualizations that users can further customize if necessary. This platform excels at creating and designing reports, then distributing them either at-will or through the automated scheduling tool, as noted by a majority of users who reviewed reporting. Most notably, the platform has an outstanding support team - all of the users who reviewed its support expressed satisfaction with their proactive, responsive assistance, citing the vendor’s dedication to the success of their customers as notably apparent. Customers can tailor the platform to their needs, as its flexibility allows for customized solutions. Frequent updates add value over time, though some users remarked that these sometimes break features from older versions. Other performance issues noted in reviews include lags when performing complex queries, infrequent crashes, slow load times and issues when accessing the platform from specific devices or browsers. While easy to pick up and use, especially for the end-user, some reviewers said that there is a learning curve to master the many features of this tool — a few users noted that this learning curve lasted a few months for some team members in their organizations. Overall, WebFOCUS is a worthy pick for self-service data visualization and reporting, especially in the hands of an organization willing to invest the resources and time to make it shine.

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Bigquery is a scalable big data warehouse solution. It enables users to pull correlated data streams using SQL like queries. Queries are executed fast regardless of the size of the datasets. It manages the dynamic distribution of workloads across computational clusters. The easy-to-navigate UI is robust and allows the user to create and execute machine learning models seamlessly. Users liked that it can connect to a variety of data analytics and visualization tools. However, users complained that query optimization is an additional hassle they have to deal with, as the solution is expensive and poorly constructed queries can quickly accumulate charges. It can be overwhelming for the non-technical user, and SQL coding knowledge is required to leverage its data analysis capabilities. Data visualization features are lacking and in need of improvement.

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SAS Viya is an AI-powered data management and visual analytics platform with a robust, scalable architecture. All users who reviewed data source connectivity said that it connects to multiple sources and integrates easily with business applications, giving a seamless user experience. With fast in-memory processing of big data sets, it leverages the power of R to enable visual statistics. All users who mentioned predictive analysis said that it enables automated forecasting through what-if scenarios, goal-seeking, text mining and decision trees. Citing ease of use, all users say that the platform is intuitive and enables easy data modeling and self-service visual analytics. All users who mentioned support said that they are responsive and knowledgeable. Around 71% of the users who comment on its functionality say that it is a robust, scalable and flexible platform that enables visualization and analysis of business data, though some users say visual statistics need improvement. On the flip side, all users who review its cost say that the tool is expensive. In summary, SAS Viya is an analytics tool that provides data management, visualization and AI-powered analytics to enterprises for improved decision making, though small organizations and startups might find it cost-prohibitive.

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Hadoop has been making waves in the Big Data Analytics scene, and for good reason. Users rave about its ability to scale like a champ, handling massive datasets that would make other platforms sweat. Its flexibility is another major plus, allowing it to adapt to different data formats and processing needs without breaking a sweat. And let's not forget about reliability – Hadoop is built to keep on chugging even when things get rough. However, it's not all sunshine and rainbows. Some users find Hadoop's complexity a bit daunting, especially if they're new to the Big Data game. The learning curve can be steep, so be prepared to invest some time and effort to get the most out of it. So, who's the ideal candidate for Hadoop? Companies dealing with mountains of data, that's who. If you're in industries like finance, healthcare, or retail, where data is king, Hadoop can be your secret weapon. It's perfect for tasks like analyzing customer behavior, detecting fraud, or predicting market trends. Just remember, Hadoop is a powerful tool, but it's not a magic wand. You'll need a skilled team to set it up and manage it effectively. But if you're willing to put in the work, Hadoop can help you unlock the true potential of your data.

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Related Categories

Top Alternatives in Big Data Analytics Tools


Azure Synapse Analytics

Dataiku

H2O.ai

IBM Watson Studio

KNIME

Looker Studio

Oracle Analytics Cloud

Qlik Sense

RapidMiner

SageMaker

SAP Analytics Cloud

SAS Viya

Spotfire

Tableau

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