

Find out what your peers are saying about Apache, Cloudera, Amazon Web Services (AWS) and others in Hadoop.
I would rate the technical support of Apache Spark an eight because when we had questions, we found solutions, and it was straightforward.
I have received support via newsgroups or guidance on specific discussions, which is what I would expect in an open-source situation.
Apache Spark resolves many problems in the MapReduce solution and Hadoop, such as the inability to run effective Python or machine learning algorithms.
Without a doubt, we have had some crashes because each situation is different, and while the prototype in my environment is stable, we do not know everything at other customer sites.
It can handle large datasets.
I find that there really lacks the technical depth to do any recommendations for future updates of Apache Spark.
Various tools like Informatica, TIBCO, or Talend offer specific aspects, licensing can be costly;
Pentaho Business Analytics is hard to learn and not suited for initial users as it requires knowledge of operating systems, Java, and other technical skills.
Pentaho Business Analytics is priced similarly to other competitors such as QlikView and Tableau.
The most important part is that everything can be connected, and the data exchange across overseas connections is fast and reliable.
Apache Spark is the solution, and within it, you have PySpark, which is the API for Apache Spark to write and run Python code.
The solution is beneficial in that it provides a base-level long-held understanding of the framework that is not variant day by day, which is very helpful in my prototyping activity as an architect trying to assess Apache Spark, Great Expectations, and Vault-based solutions versus those proposed by clients like TIBCO or Informatica.
It is a stable product, and it can handle large datasets.
| Product | Mindshare (%) |
|---|---|
| Apache Spark | 14.2% |
| Cloudera Distribution for Hadoop | 14.4% |
| Amazon EMR | 10.0% |
| Other | 61.4% |
| Product | Mindshare (%) |
|---|---|
| Pentaho Business Analytics | 1.0% |
| Microsoft Power BI | 7.4% |
| Tableau Enterprise | 5.9% |
| Other | 85.7% |

| Company Size | Count |
|---|---|
| Small Business | 28 |
| Midsize Enterprise | 16 |
| Large Enterprise | 33 |
| Company Size | Count |
|---|---|
| Small Business | 22 |
| Midsize Enterprise | 7 |
| Large Enterprise | 15 |
Apache Spark is a leading open-source processing tool known for scalability and speed in managing large datasets. It supports both real-time and batch processing and is widely used for building data pipelines, machine learning applications, and analytics.
Apache Spark's strengths lie in its ability to process large data volumes efficiently through real-time and batch capabilities. With in-memory computation, it ensures fast data processing and significant performance gains. Its wide range of APIs, including those for machine learning, SQL, and analytics, make it versatile in handling complex data operations. While popular for ease of use and fault tolerance, Spark's management, debugging, and user-friendliness could benefit from improvements. Better GUIs, integration with BI tools, and enhanced monitoring are desired, alongside shuffling optimization and compatibility with more programming languages.
What are Apache Spark's key features?Organizations use Apache Spark predominantly for in-memory data processing, enabling seamless integration with big data frameworks. It's applied in security analytics, predictive modeling, and helps facilitate secure data transmissions in AI deployments. Industries leverage Spark's speed for sentiment analysis, data integration, and efficient ETL transformations.
Pentaho Business Analytics, recognized for its powerful ETL capabilities, delivers robust data management and analytics. Its adaptable interface and custom plugins enable effective data transformations, appealing to enterprises seeking efficient data handling and integration.
Pentaho Business Analytics offers a comprehensive suite for data warehousing, ETL processes, and business intelligence. Known for integrating and analyzing data from multiple systems, it supports industries like marketing, automotive, telecom, and insurance. Despite critiques on its interface and Java reliance, its ability to manage both small and complex data loads makes it a cost-effective choice.
What are the key features of Pentaho Business Analytics?Pentaho Business Analytics finds application in sectors requiring extensive data storage and management like telecom and insurance. Companies utilize its capabilities for creating ETL pipelines, managing data flows, and enabling data-driven decision-making.
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