--- description: Compare the top 2026 Starburst alternatives. See analyst ratings, pricing, and features for competing Big Data Analytics Tools to find your perfect fit. Compare now! --- [Home](https://www.selecthub.com/) > [Big Data](https://www.selecthub.com/research/big-data-analytics/) > [Big Data Analytics Tools](https://www.selecthub.com/c/big-data-analytics-tools/) > [Starburst](https://www.selecthub.com/p/big-data-analytics-tools/starburst-data/) > Starburst Alternatives # Top Starburst Alternatives & Competitors For 2026 Last Updated: October 29th, 2026 We compared **[Starburst](https://www.selecthub.com/p/big-data-analytics-tools/starburst-data/)** against four alternatives worth considering, so you can see where each one shines and where it falls short. Our comparison is based on user reviews and publicly available information about each product’s features and pricing. Remove Add to Compare Select Product Alteryx Apache Pig Azure Data Lake Azure Databricks Azure Synapse Analytics dbt Labs Exasol Gigasheet Hadoop KNIME Looker Studio Oracle Analytics Cloud Qlik Sense RapidMiner SAP Analytics Cloud SAS Viya Spark Spotfire Starburst Tableau [![Starburst Software Tool](https://cdn.selecthub.com/products/e6dc5789517d0ecd1b071903c4810eaa-13a1fae9b82409212cde87b7ba8e5fe9/resources/original/logo.svg?1747072733)](https://www.selecthub.com/p/big-data-analytics-tools/starburst-data/) Remove Add to Compare Select Product Alteryx Apache Pig Azure Data Lake Azure Databricks Azure Synapse Analytics dbt Labs Exasol Gigasheet Hadoop KNIME Looker Studio Oracle Analytics Cloud Qlik Sense RapidMiner SAP Analytics Cloud SAS Viya Spark Spotfire Starburst Tableau [![Hadoop Software Tool](https://cdn.selecthub.com/products/6624b6d8217cf71640993409df58204f-16671a3fb94595bf3a6ca6430fdf4796/resources/normal/logo.png?1693317007)](https://www.selecthub.com/p/big-data-analytics-tools/hadoop/) Remove Add to Compare Select Product Alteryx Apache Pig Azure Data Lake Azure Databricks Azure Synapse Analytics dbt Labs Exasol Gigasheet Hadoop KNIME Looker Studio Oracle Analytics Cloud Qlik Sense RapidMiner SAP Analytics Cloud SAS Viya Spark Spotfire Starburst Tableau [![Azure Databricks Software Tool](https://cdn.selecthub.com/products/d6dabcc412981d56c8733b52586a9d44-62726b52767496268ddc9621ec45ab17/resources/normal/logo.png?1693318095)](https://www.selecthub.com/p/big-data-analytics-tools/azure-databricks/) Remove Add to Compare Select Product Alteryx Apache Pig Azure Data Lake Azure Databricks Azure Synapse Analytics dbt Labs Exasol Gigasheet Hadoop KNIME Looker Studio Oracle Analytics Cloud Qlik Sense RapidMiner SAP Analytics Cloud SAS Viya Spark Spotfire Starburst Tableau [![Apache Pig Software Tool](https://cdn.selecthub.com/products/c900fe92840c527a0c54f28640c2f254-4be455a586ffbeaf103927f9b8dcd076/resources/normal/logo.png?1693318193)](https://www.selecthub.com/p/big-data-analytics-tools/apache-pig/) Remove Add to Compare Select Product Alteryx Apache Pig Azure Data Lake Azure Databricks Azure Synapse Analytics dbt Labs Exasol Gigasheet Hadoop KNIME Looker Studio Oracle Analytics Cloud Qlik Sense RapidMiner SAP Analytics Cloud SAS Viya Spark Spotfire Starburst Tableau [![dbt Labs Software Tool](https://cdn.selecthub.com/products/7bc22204fbaa5ff29a4e5a64f77dde89-03c4b9966bd1d604a2851d7f8abd57af/resources/original/logo.svg?1747073689)](https://www.selecthub.com/p/big-data-analytics-tools/dbt-labs/) [![Product Awards](https://www.selecthub.com/display/images/awards_badge.svg)](#awards-section) [Get Free Demo](https://pmo.selecthub.com/get-product-demo/?category=Big+Data+Analytics+Tools&product_name=Starburst&product_logo=https%3A%2F%2Fd3uimxdj41cg3o.cloudfront.net%2Fproducts%2Fe6dc5789517d0ecd1b071903c4810eaa-13a1fae9b82409212cde87b7ba8e5fe9%2Fresources%2Foriginal%2Flogo.svg%3F1747072733) [Get Free Demo](https://pmo.selecthub.com/get-product-demo/?category=Big+Data+Analytics+Tools&product_name=Hadoop&product_logo=https%3A%2F%2Fd3uimxdj41cg3o.cloudfront.net%2Fproducts%2F6624b6d8217cf71640993409df58204f-16671a3fb94595bf3a6ca6430fdf4796%2Fresources%2Fnormal%2Flogo.png%3F1693317007) [Get Free Demo](https://pmo.selecthub.com/get-product-demo/?category=Big+Data+Analytics+Tools&product_name=Azure%2BDatabricks&product_logo=https%3A%2F%2Fd3uimxdj41cg3o.cloudfront.net%2Fproducts%2Fd6dabcc412981d56c8733b52586a9d44-62726b52767496268ddc9621ec45ab17%2Fresources%2Fnormal%2Flogo.png%3F1693318095) [Get Free Demo](https://pmo.selecthub.com/get-product-demo/?category=Big+Data+Analytics+Tools&product_name=Apache%2BPig&product_logo=https%3A%2F%2Fd3uimxdj41cg3o.cloudfront.net%2Fproducts%2Fc900fe92840c527a0c54f28640c2f254-4be455a586ffbeaf103927f9b8dcd076%2Fresources%2Fnormal%2Flogo.png%3F1693318193) [Get Free Demo](https://pmo.selecthub.com/get-product-demo/?category=Big+Data+Analytics+Tools&product_name=dbt%2BLabs&product_logo=https%3A%2F%2Fd3uimxdj41cg3o.cloudfront.net%2Fproducts%2F7bc22204fbaa5ff29a4e5a64f77dde89-03c4b9966bd1d604a2851d7f8abd57af%2Fresources%2Foriginal%2Flogo.svg%3F1747073689) ### Product Insights Product Ranking ## #13 among all Big Data Analytics Tools ## #1 among all Big Data Analytics Tools ## #9 among all Big Data Analytics Tools ## #16 among all Big Data Analytics Tools ## #7 among all Big Data Analytics Tools [Find out who the leaders are](https://pmo.selecthub.com/request-custom-scorecard?post_type=alt_article&name=big-data-analytics-tools__starburst-data&category_slug=big-data-analytics-tools&product_slug=starburst-data) Price Starts From $0.50/Credit, Usage-Based [Free Trial is available →]() Custom Quote  i Free Trial is unavailable → Custom Quote  i [Free Trial is available →]() $0 Free, Open-Source Free Trial is unavailable → $100/Seat, Monthly, Freemium [Free Trial is available →]() Pros - **Unified Data Access:** Starburst allows you to query data across all sources, eliminating the need to move data to a central location. - **Fast Performance:** Starburst leverages a high-performance distributed SQL engine to provide fast query results, even with large datasets. - **Strong Security:** Starburst offers enterprise-grade security features, including fine-grained access control and integration with authentication systems, making it suitable for businesses with strict security requirements. - **Flexible Deployment:** Starburst can be deployed on various platforms, including hybrid, multi-cloud, and on-premises environments, providing flexibility in choosing the best deployment model for your needs. - **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. - **Ease of Use:** Azure Databricks is lauded for its user-friendly design, which makes it simpler for teams to perform big data analytics, even without extensive technical expertise. - **Azure Integration:** User reviews highlight the seamless integration with other Azure services, such as Azure Data Lake Storage, streamlining data workflows. - **Programming Language Support:** The platform's compatibility with multiple programming languages, including Python, Scala, and R, is frequently cited as a benefit by users. - **Scalability:** Azure Databricks, powered by Apache Spark, receives praise for its ability to scale resources, allowing it to handle large datasets and complex analytical tasks efficiently. - **Ease of Use:** User reviews highlight Pig Latin's simple syntax as a key factor in its ease of use, especially for users without extensive Java knowledge. This allows for quicker development and execution of data processing tasks. - **Optimized for Hadoop:** Apache Pig is specifically designed for the Hadoop ecosystem, seamlessly integrating with HDFS and MapReduce for efficient processing of large datasets. - **Handles Large Datasets:** User reviews often mention Pig's ability to efficiently process and analyze massive datasets, making it suitable for big data analytics needs. - **Improved Data Quality:** User reviews highlight that dbt Labs' software helps improve data quality through features like automated testing and data lineage tracking. - **Enhanced Productivity:** User reviews praise dbt's ability to streamline data transformation processes, enabling data teams to work more efficiently and productively. They specifically mention that dbt's use of SQL, a language familiar to many data professionals, contributes to this efficiency. - **Seamless Collaboration:** User reviews emphasize dbt's role in fostering collaboration among data teams. Features like version control and shared documentation facilitate better teamwork and knowledge sharing. Cons - **Resource Consumption:** Starburst may consume significant resources, potentially impacting performance when handling very large datasets, as highlighted in user reviews. - **System Complexity:** Setting up and configuring Starburst can be complex, demanding a longer initial training period for new users, according to user reviews. - **Query Window Limitation:** A user review mentioned the inconvenience of the query window closing without automatically saving work, potentially leading to loss of progress. - **Complex Query Performance:** Some user reviews indicated that very complex queries could sometimes lead to performance issues and slow down the system. - **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. - **Cost of DBUs:** While Azure Databricks offers a quick Spark setup, the cost of Databricks Units (DBUs) can accumulate significantly, especially for larger jobs, as highlighted in user reviews. - **Falling Behind:** User reviews reflect that Apache Pig's popularity has decreased as newer technologies like Apache Spark have emerged, offering more features and better performance. - **Performance Bottlenecks:** As per user reviews, while Pig simplifies MapReduce, complex tasks, especially with skewed data, can still face performance issues, making it less efficient than writing custom MapReduce jobs in certain scenarios. - **Pricing:** User reviews have noted that dbt Labs' pricing model, particularly for dbt Cloud, has become a point of contention due to its inflexible structure and recent price increases. - **Operational Reporting:** dbt Labs primarily focuses on data transformation and may require additional tools for comprehensive operational reporting, potentially leading to increased complexity and costs for businesses. ### Our Review Is Starburst the "star" performer when it comes to Big Data Analytics, or does it fizzle out? User reviews from the past year indicate that Starburst shines brightly in several key areas. Its ability to connect to and query data from various sources, like relational databases and cloud storage, without needing to move the data, is a major plus. Users rave about how this "single point of access" simplifies their analytics workflow and eliminates the need for time-consuming data transfers. For instance, one user highlighted how Starburst's data lakehouse architecture allows them to seamlessly query data across different formats and locations, significantly speeding up data analysis for their team. However, some users have pointed out that Starburst can be a resource hog, especially when dealing with massive datasets, leading to potential performance hiccups and higher costs. One user specifically mentioned the need for careful resource management policies to avoid unexpectedly high compute costs. Think of it like a powerful engine that, while capable of incredible speed, can guzzle fuel if not handled carefully. Despite this drawback, Starburst's strengths, particularly its unified data access, high performance, and robust security features, make it a compelling choice for organizations looking to streamline their Big Data Analytics. Its ability to handle complex queries across diverse data sources at scale makes it particularly well-suited for data-driven businesses in need of a robust and scalable analytics solution. Show more 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. Show more Is Azure Databricks truly a brick house when it comes to handling big data, or will it crumble under pressure? User reviews from the last year suggest that Azure Databricks is a robust and reliable platform for big data analytics. Users consistently highlight its seamless integration with Apache Spark as a key strength, enabling lightning-fast data processing and analysis. This integration, coupled with its intuitive interface, makes it a favorite among both seasoned data scientists and those new to the field. Azure Databricks's scalability is another major selling point. Users praise its ability to effortlessly handle massive datasets, making it suitable for organizations of all sizes. However, some users have reported mixed experiences with customer service, which could be an area for improvement. Overall, Azure Databricks emerges as a top contender in the big data analytics arena, particularly well-suited for organizations dealing with large and complex datasets that demand speed and efficiency. Show more Is Apache Pig hogwash or the gold standard in the world of Big Data? While not exactly the latter, Apache Pig has its place. Users consistently praise Apache Pig for its user-friendly scripting language, Pig Latin, which simplifies complex data transformations, making it a more accessible alternative to writing intricate MapReduce programs in Java. For instance, tasks like filtering and aggregating large datasets can be achieved with significantly less code compared to traditional MapReduce, allowing users to focus on data analysis rather than intricate programming details. This simplicity makes it particularly appealing for users without deep Java expertise, enabling them to quickly adapt and become productive in a Hadoop environment.However, Apache Pig's limitations are also apparent in user feedback. A recurring concern is its performance, particularly when handling smaller datasets where it can feel sluggish compared to more modern alternatives like Apache Spark. Additionally, the implicit data schema, while simplifying development, can sometimes lead to runtime errors that are difficult to debug. This lack of strict type checking during compilation can be a pain point for users accustomed to more robust data validation in other tools. In conclusion, Apache Pig is best suited for organizations deeply entrenched in the Hadoop ecosystem, particularly those dealing with large datasets and requiring a simpler alternative to Java-based MapReduce programming. Its strength lies in its ability to streamline ETL processes and empower users with varying technical backgrounds to perform data manipulations efficiently. However, its limitations in performance, particularly with smaller datasets, and the potential for runtime errors due to its implicit data schema, make it a less attractive option for organizations seeking cutting-edge performance or working with more dynamic data environments. Show more Is dbt Labs all it's hyped up to be, or does it need more time to bake? User reviews from the last year tell a tale of a product that's transforming the way data teams work, but not without a few caveats. dbt Labs excels in its ability to bring software engineering best practices to the world of data transformation. Users rave about its SQL-based approach, which makes it easy for analysts and engineers to define and manage complex data pipelines using a language they already know. This, coupled with its modularity, version control, and testing capabilities, makes dbt Labs a favorite for teams looking to build scalable and maintainable analytics pipelines. For instance, users highlight the ease of reusing data models, automating schema testing, and generating documentation, which significantly speeds up development and reduces errors. However, some users express concerns about dbt Cloud's pricing structure, finding it potentially expensive for certain teams or projects. Additionally, while dbt Labs excels in SQL-based transformations, its support for non-SQL tasks might be limited, potentially requiring additional tools for specific use cases. Overall, dbt Labs emerges as a must-have for data teams, particularly those dealing with large volumes of data and complex transformations. Its SQL-centric approach, coupled with its focus on collaboration, testing, and automation, makes it a powerful tool for building robust and scalable data pipelines. However, potential users should carefully evaluate dbt Cloud's pricing structure against their needs and consider whether its SQL-focused approach aligns with their specific data transformation requirements. Show more ### User Sentiment Summary Starburst has a user sentiment rating of 87 based on 132 reviews. Hadoop has a user sentiment rating of 85 based on 474 reviews. Azure Databricks has a user sentiment rating of 88 based on 197 reviews. Apache Pig has a user sentiment rating of 81 based on 43 reviews. dbt Labs has a user sentiment rating of 95 based on 249 reviews. ![Great User Sentiment](https://www.selecthub.com/display/images/scores/great.svg) 132 reviews ![Great User Sentiment](https://www.selecthub.com/display/images/scores/great.svg) 474 reviews ![Great User Sentiment](https://www.selecthub.com/display/images/scores/great.svg) 197 reviews ![Great User Sentiment](https://www.selecthub.com/display/images/scores/great.svg) 43 reviews ![Excellent User Sentiment](https://www.selecthub.com/display/images/scores/excellent.svg) 249 reviews Synopsis Evaluating all review platforms, our market analysts have compiled the following user sentiment data. 87% *of users recommend this product* Starburst has a 'great' User Satisfaction Rating of 87% when considering 132 user reviews from 2 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. 88% *of users recommend this product* Azure Databricks has a 'great' User Satisfaction Rating of 88% when considering 197 user reviews from 4 recognized software review sites. 81% *of users recommend this product* Apache Pig has a 'great' User Satisfaction Rating of 81% when considering 43 user reviews from 2 recognized software review sites. 95% *of users recommend this product* dbt Labs has a 'excellent' User Satisfaction Rating of 95% when considering 249 user reviews from 3 recognized software review sites. User Review Scores**G2.com, Inc** **4.3** (88) **4.3** (101) **4.4** (114) **3.9** (21) **4.8** (173) **Capterra Inc** n/a **4.3** (244) **4.5** (15) n/a n/a **Gartner, Inc** **4.5** (44) n/a **4.4** (28) n/a **4.7** (19) **TrustRadius** n/a **4.2** (129) **4.3** (40) **4.2** (22) n/a **Spiceworks Inc** n/a n/a n/a n/a **4.6** (57) ### Awards SelectHub awards earned by these products based on a comprehensive analysis by our research analysts. No awards. No awards. No awards. No awards. ![User Favorite Award](<> "User Favorite Award") ### Product Assistance Training Resources Documentation In Person Live Online Videos Webinars Documentation In Person Live Online Videos Webinars Documentation In Person Live Online Videos Webinars Documentation In Person Live Online Videos Webinars Documentation In Person Live Online Videos Webinars Support Email Phone Chat FAQ Forum Help Desk Knowledge Base Tickets Training 24/7 Live Support Email Phone Chat FAQ Forum Help Desk Knowledge Base Tickets Training 24/7 Live Support Email Phone Chat FAQ Forum Help Desk Knowledge Base Tickets Training 24/7 Live Support Email Phone Chat FAQ Forum Help Desk Knowledge Base Tickets Training 24/7 Live Support Email Phone Chat FAQ Forum Help Desk Knowledge Base Tickets Training 24/7 Live Support ### Product Basics Company Size i Small Medium Large Small Medium Large Small Medium Large Small Medium Large Small Medium Large Platforms Supported Windows Mac Linux Android Chromebook Windows Mac Linux Android Chromebook Windows Mac Linux Android Chromebook Windows Mac Linux Android Chromebook Windows Mac Linux Android Chromebook Deployment Supported Cloud On-Premise Mobile Cloud On-Premise Mobile Cloud On-Premise Mobile Cloud On-Premise Mobile Cloud On-Premise Mobile ### Top Alternatives in Big Data Analytics Tools [![Alteryx Software Tool]()--- Alteryx](https://www.selecthub.com/p/big-data-analytics-tools/alteryx/) [![Azure Synapse Analytics Software Tool]()--- Azure Synapse Analytics](https://www.selecthub.com/p/big-data-analytics-tools/azure-synapse-analytics/) [![Dataiku Software Tool]()--- Dataiku](https://www.selecthub.com/p/big-data-analytics-tools/dataiku/) [![H2O.ai Software Tool]()--- H2O.ai](https://www.selecthub.com/p/big-data-analytics-tools/h2o-ai/) [![IBM Watson Studio Software Tool]()--- IBM Watson Studio](https://www.selecthub.com/p/big-data-analytics-tools/ibm-watson-studio/) [![KNIME Software Tool]()--- 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Spotfire](https://www.selecthub.com/p/data-visualization-tools/spotfire/) [![Tableau Software Tool]()--- Tableau](https://www.selecthub.com/p/business-intelligence-tools/tableau/) ### Related Categories These products can also be found with other leading products in these categories: we're gathering data Show more [Business Analytics Tools](https://www.selecthub.com/c/business-analytics-tools/) Show more [Data Warehouse Reporting Tools](https://www.selecthub.com/c/data-warehouse-reporting-tools/) [Data Warehouse Tools](https://www.selecthub.com/c/data-warehouse-tools/) Show more we're gathering data Show more we're gathering data Show more ### Compare other software products using the SelectHub platform Select a Category 360 Degree Feedback Software 3D Design Software 3PL Software ABA Software Account-Based Marketing Software Accounting Practice Management Software Accounting Software Accounts Payable Software Accounts Receivable Software Agile Project Management Software AI Agent 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Our market data is crowdsourced from our user-base of 100,000+ companies. WE DISTILL IT INTO REAL REQUIREMENTS, COMPARISON REPORTS, PRICE GUIDES and more... ![SelectHub Products Reporting and Analytics]() [Build Your Requirements](https://pmo.selecthub.com/big-data-requirements-onsite/) ![SelectHub Products Cost and Pricing Guide]() [Get Your Free Comparison Report](https://pmo.selecthub.com/request-custom-scorecard/?category=Big%20Data%20Analytics%20Tools) **Supported:** Fully or moderately supported out-of-the-box with industry-leading capabilities and is immediately available after installation without needing any add-ons, integrations, or custom development. **Not Supported:** Not directly available in the software, but can be accomplished using other built-in features, workarounds, or add-ons/products from the vendor at an additional cost. At most, requires additional integrations, plugins, marketplace applications from a third-party vendor, or custom development using the APIs, libraries, extensions, and development framework supported by the software, with or without any additional cost. Close ```json { "@context": "https://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": 1, "name": "Home", "item": "https://www.selecthub.com/" }, { "@type": "ListItem", "position": 2, "name": "Big Data", "item": "https://www.selecthub.com/research/big-data-analytics/" }, { "@type": "ListItem", "position": 3, "name": "Big Data Analytics Tools", "item": "https://www.selecthub.com/c/big-data-analytics-tools/" }, { "@type": "ListItem", "position": 4, "name": "Starburst", "item": "https://www.selecthub.com/p/big-data-analytics-tools/starburst-data/" }, { "@type": "ListItem", "position": 5, "name": "Starburst Alternatives" } ] } ```