We performed a comparison between Amazon EC2, Apache Spark, and Azure Stream Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Amazon Web Services (AWS), Apache, Zadara and others in Compute Service."The product helps us with scalability. We also need not have data centers."
"The most valuable feature of Amazon EC2 is its ability to spin a new virtual machine in a few seconds."
"The flexibility of the security features is what is interesting."
"The most valuable feature of this solution is the ability to have standard operating systems along with the Windows, Linux operating systems, and their maintenance-free structure, which we prefer."
"The ethernet configuration is stable and the product is reliable."
"The most valuable features of Amazon EC2 are content delivery and adaptability."
"The initial setup is straightforward."
"I use it for NextCloud and for developer purposes."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"I appreciate everything about the solution, not just one or two specific features. The solution is highly stable. I rate it a perfect ten. The solution is highly scalable. I rate it a perfect ten. The initial setup was straightforward. I recommend using the solution. Overall, I rate the solution a perfect ten."
"With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware."
"The most crucial feature for us is the streaming capability. It serves as a fundamental aspect that allows us to exert control over our operations."
"The fault tolerant feature is provided."
"ETL and streaming capabilities."
"The solution has been very stable."
"Now, when we're tackling sentiment analysis using NLP technologies, we deal with unstructured data—customer chats, feedback on promotions or demos, and even media like images, audio, and video files. For processing such data, we rely on PySpark. Beneath the surface, Spark functions as a compute engine with in-memory processing capabilities, enhancing performance through features like broadcasting and caching. It's become a crucial tool, widely adopted by 90% of companies for a decade or more."
"The solution's most valuable feature is its ability to create a query using SQ."
"The integrations for this solution are easy to use and there is flexibility in integrating the tool with Azure Stream Analytics."
"We find the query editor feature of this solution extremely valuable for our business."
"I like all the connected ecosystems of Microsoft, it is really good with other BI tools that are easy to connect."
"The solution has a lot of functionality that can be pushed out to companies."
"The most valuable features are the IoT hub and the Blob storage."
"Provides deep integration with other Azure resources."
"It provides the capability to streamline multiple output components."
"EC2 could be improved with easier migration."
"It is a little too expensive."
"An area for improvement in Amazon EC2 is the cost because it's a bit higher than competitor pricing."
"In terms of improvement, they could build some client-side desktop tools that provide easier connectivity to Amazon."
"The initial setup could be easier because many keys are required for access."
"The ease of migrating applications could be improved."
"Amazon EC2 could improve by reducing the price."
"Pricing-wise, it is a bit high."
"The setup I worked on was really complex."
"We use big data manager but we cannot use it as conditional data so whenever we're trying to fetch the data, it takes a bit of time."
"Apache Spark could potentially improve in terms of user-friendliness, particularly for individuals with a SQL background. While it's suitable for those with programming knowledge, making it more accessible to those without extensive programming skills could be beneficial."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"Stability in terms of API (things were difficult, when transitioning from RDD to DataFrames, then to DataSet)."
"When you want to extract data from your HDFS and other sources then it is kind of tricky because you have to connect with those sources."
"The initial setup was not easy."
"The graphical user interface (UI) could be a bit more clear. It's very hard to figure out the execution logs and understand how long it takes to send everything. If an execution is lost, it's not so easy to understand why or where it went. I have to manually drill down on the data processes which takes a lot of time. Maybe there could be like a metrics monitor, or maybe the whole log analysis could be improved to make it easier to understand and navigate."
"Early in the process, we had some issues with stability."
"Sometimes when we connect Power BI, there is a delay or it throws up some errors, so we're not sure."
"If something goes wrong, it's very hard to investigate what caused it and why."
"There may be some issues when connecting with Microsoft Power BI because we are providing the input and output commands, and there's a chance of it being delayed while connecting."
"The solution’s customer support could be improved."
"One area that could use improvement is the handling of data validation. Currently, there is a review process, but sometimes the validation fails even before the job is executed. This results in wasted time as we have to rerun the job to identify the failure."
"Its features for event imports and architecture could be enhanced."
"The solution doesn't handle large data packets very efficiently, which could be improved upon."
