Looking for alternatives to Hadoop? 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 Hadoop to leading industry alternatives like WebFOCUS, BigQuery, MATLAB, and Looker Studio.
Analyst Rating
User Sentiment
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.
among all Big Data Analytics Tools
Hadoop has a 'great' User Satisfaction Rating of 85% when considering 474 user reviews from 3 recognized software review sites.
WebFOCUS has a 'great' User Satisfaction Rating of 87% when considering 439 user reviews from 5 recognized software review sites.
BigQuery has a 'excellent' User Satisfaction Rating of 90% when considering 724 user reviews from 3 recognized software review sites.
MATLAB has a 'excellent' User Satisfaction Rating of 92% when considering 4535 user reviews from 5 recognized software review sites.
Looker Studio has a 'great' User Satisfaction Rating of 86% when considering 1074 user reviews from 3 recognized software review sites.
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.
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.
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.
MATLAB is a computing and programming tool that combines the power of functions and algorithms with data integration, modeling and visualization for predictive business data analysis. Users perform complex computations on data sets that the platform ingests from a multitude of data sources to glean business-specific metrics. Citing online communities, all users who reviewed support said that the tool is accessible to beginners, while providing enough depth for advanced users, though some said that the coding syntax could be daunting for non-technical users initially. Around 92% of users who reviewed its analytical capabilities said that the platform provides a wide range of built-in packages to provide out-of-the-box data analysis solutions. With its minimal scripting, many users who discussed data processing said that they could simulate complex mathematical functions to visualize complex data models. Reviewing its functionality, many users said that its rich library and design makes it possible to write powerful programs easily. A majority of users who discussed its performance said that the platform consumes a lot of power and space and slows down when performing complex computations, possibly because updates, though frequent, do not include optimization for older features. Many users who reviewed the cost said that individual user licenses are expensive, and buying additional libraries adds to the cost since many of these have interlinking dependencies, though some users said that the platform provides value for money. In summary, MATLAB is a programming solution that leverages machine learning for data collection and complex computations for users to create data models and visualize enterprise metrics for predictive analysis.
User reviews for Google Looker Studio indicate both strengths and weaknesses. Many users praise its intuitive interface, which simplifies data analysis. The platform's powerful visualization tools and real-time insights are widely appreciated, enabling users to present and act on data effectively. Collaboration features also receive positive feedback, facilitating teamwork and informed decision-making. However, several users highlight challenges. A notable drawback is the steep learning curve, especially for those without SQL or data analysis skills. Some users find data integration complex and resource-intensive, potentially impacting performance. Cost considerations also arise, with users noting that Looker Studio's pricing may not align with all budgets. In comparison to similar products, Looker Studio stands out for its user-friendly interface and strong visualization capabilities. However, some users mention limitations in offline functionality, which competitors may handle better. Overall, Google Looker Studio appears to be a valuable tool for data analysis and collaboration, but it may require a learning curve and careful consideration of budget constraints.
WE DISTILL IT INTO REAL REQUIREMENTS, COMPARISON REPORTS, PRICE GUIDES and more...