Top Cloudera Alternatives & Competitors For 2024

Is Cloudera the answer to your data management woes, or is it just a bunch of hot air? User reviews from the past year paint a mixed picture of Cloudera. While some users praise its flexibility and ability to handle large datasets, others find it cumbersome and expensive. Cloudera's hybrid cloud approach, allowing users to deploy on-premises or in the cloud, is a major selling point for many. However, some users find the platform's complexity a barrier to entry, especially for those without extensive experience in data management. Cloudera's integration with other tools, such as Apache Hadoop, is a key differentiator, but some users report issues with compatibility and performance. Cloudera is best suited for large enterprises with complex data needs and a dedicated team of data engineers. Its robust features and scalability make it a powerful tool for organizations that require a comprehensive data management solution. However, smaller businesses or those with limited technical resources may find Cloudera's complexity and cost prohibitive.

Our researchers ranked products on a whole bunch of features. They include data management, querying and visualization, advanced and embedded analytics, mobile BI, and IoT and location analytics.In our rankings, Power BI scores 87 for connectivity, leaving behind Tableau, Oracle Analytics and Dundas BI. Robust Microsoft technology is one reason, for sure. Besides, intelligent techniques like DirectQuery and easy data modeling make it popular among users.In product reviews, some users mentioned a lag when sharing reports from the desktop to the cloud. For me, the platform was a tad slow to start, but otherwise, it stayed performant for my average-sized dataset.When dealing with sales data, total sales, the top-performing products, seasonality and period trends are common queries. Creating a sales KPI report in Power BI was an excellent way for me to answer them. My CSV files included sales, calendar, products and store data.Connecting to sources is straightforward with Get Data on the home screen and toolbar. Once I had pulled in the data, I clicked on Transform Data and opened the Power Query editor. It automatically detects the data type for strings and numbers but can get confused with dates and currency, which it marks as text. It involved some manual wrangling, but I had it sorted in no time. Read my article on KPI Reports to learn how I did it.But I wouldn’t call it a deal-breaker as it’s not a tedious task. I had the same experience with Qlik Sense, but Tableau was way better as it recognizes seven data types — string, number, date, date and time, boolean, geographic and cluster values.Tracking sales over periods required a greater level of detail, so I added new columns to the calendar data — start of month and start of week. Column statistics were immensely helpful in identifying unique, distinct and null values and correcting incomplete records. Clicking on the number of products selling at a particular price allowed me to see which toys sold at that price.Creating a relational data model by defining primary keys is a manual process and seems dated once you’ve used Qlik Sense. Adding calculated measures is where DAX shows its magic. For data workers well-versed with SQL, DAX is a ready-to-go tool they’ll be glad to have in their corner.Creating visualizations wasn’t as intuitive as Tableau as it involved drag-and-drop onto the canvas, and frankly, I felt like I was flying blind. I didn’t feel that way with Tableau, and it’s slicker.Power BI offers a paintbrush tool that lets you define the layout, the card arrangement and the maximum number of cards. You can define the canvas settings, background and headers and determine the filter pane settings. It took me longer to create a dashboard from scratch than it took in Tableau.Some users found the pricing structure too complex. While using Azure data in Power BI for basic queries is free, costs can add up when you go for text and sentiment analysis. With Microsoft Fabric, the pricing complexity is set to rise. Though Power BI is available separately too, you’ll need to rely on Fabric to manage users, licenses and other administrative tasks.About 31% of the users mentioning cost complained about onboarding difficulties, possibly because DAX introduces the complexity of learning syntax. It can daunt non-technical users initially, but guided formulas can make the task easier. That said, I agree with the majority of user reviews that training will speed up onboarding and help your team maximize the investment.Overall, Power BI has many powerful features and will give you value for your money. If you’re not a Microsoft user yet, it’s worth checking out for the baked-in vendor technologies like Azure and SSAS. If you are an MS user, Power BI might be a no-brainer, though be prepared to shell out a little extra for advanced functionality and additional modules.

Users appreciate how Sisense creates large datasets from constantly evolving data sources to be seamlessly streamlined into actionable data, and presented easily in the form of graphs, bar and pie charts, scattergrams, line graphs, interactive maps and many more visualization types. Regarding customer support, users praise their prompt and informative responses - from implementation to handling subsequent queries — as high quality customer service that comes neatly packaged with pricing plans. Users mention that the implementation of this solution, though easy for basic setup, can be quite demanding in terms of scripting and configuration setup, especially for advanced analytics. Non-technical users might find it challenging to set up the data objects - ElastiCubes - without strong IT support. On the front-end, dashboard customization and formatting of visualizations can be tricky as these require basic knowledge of CSS, Javascript and development. Though a large number of users find this solution to be cost-effective, smaller businesses and startups that only need a limited number of licenses might find it expensive. Overall, Sisense is a strong BI solution with strong data capabilities, and its drill-down functionality empowers users to glean insightful and actionable analytics that drive business strategy by aiding in decision-making processes. To maximize its potential, businesses may require strong IT support for implementation and formatting of visualizations. It is certainly worth considering for enterprise BI needs, if the price is right!

JReport is an embedded reporting and business intelligence solution that drives self-service analytics, helps users to customize interactive data dashboards and adds value to business applications via report creation and sharing. Mentioning its data connectivity capabilities, both as an embedded and a standalone solution, many users said that it integrated well with a range of data sources and embedded seamlessly into any application on any platform. Many users who discussed its functionality said that the solution was feature-rich, with intuitive capabilities such as drag-and-drop, and that it was highly scalable in implementing domain-specific features with server clustering. All users who discussed support said that they were proactive and responsive in ensuring that feature requests were added to upcoming releases. Though the platform did not seem to have any tangible limitations at the time of publishing this synopsis, some users said that there is definite room for improvement in regards to clarity of the product roadmap. Reviewing reporting, quite a few users said that the multitude of options was overwhelming and reporting features were not ubiquitous between the two modules - on the web and in the JReport desktop application. Overall, JReport embeds smoothly into business applications to enable self-service and interactive data analysis via impressive features like visualizations and report scheduling that power decision-making processes.

Let's crunch some numbers and see what users have to say about Mathematica! Mathematica has garnered a reputation as a powerful computational tool, particularly in academic and research settings. Users frequently praise its symbolic computation capabilities, allowing them to manipulate and solve complex mathematical expressions and equations with ease. This strength sets Mathematica apart from competitors like MATLAB, which primarily focuses on numerical computation. Mathematica's notebook interface also receives positive feedback for its ability to combine code, visualizations, and text in a single document, facilitating reproducible research and clear communication of findings. However, Mathematica's steep learning curve and high price point are often cited as drawbacks. Users transitioning from other programming languages may find Mathematica's syntax and functional programming paradigm challenging to grasp initially. Additionally, the cost of a Mathematica license can be prohibitive for individual users or small businesses. Overall, Mathematica is best suited for researchers, scientists, and engineers who require a comprehensive tool for symbolic and numerical computation, data analysis, and visualization. Its extensive functionality and ability to handle complex mathematical problems make it an invaluable asset in these fields. However, individuals or organizations with limited budgets or those seeking a more user-friendly option may want to explore alternative software solutions. Keep in mind that software is constantly evolving, so it's always a good idea to check for the latest updates and user reviews to make an informed decision.