We performed a comparison between Amazon Virtual Private Cloud and Apache Spark based on real PeerSpot user reviews.
Find out in this report how the two Compute Service solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Amazon Virtual Private Cloud administers an entire infrastructure in the cloud. Its ability to create subnets has been helpful for our resource deployment."
"One person with capable knowledge can implement the solution."
"It is an user-friendly solution."
"The product's initial setup phase is simple since my company manages it with the use of Terraform."
"With an AWS virtual private cloud, you're in charge of what you use. It's pay-as-you-go."
"The documentation is very clear."
"It is very easy to provision a VPC and build your network."
"The product can be used to isolate environments."
"The tool's most valuable feature is its speed and efficiency. It's much faster than other tools and excels in parallel data processing. Unlike tools like Python or JavaScript, which may struggle with parallel processing, it allows us to handle large volumes of data with more power easily."
"Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term."
"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."
"One of the key features is that Apache Spark is a distributed computing framework. You can help multiple slaves and distribute the workload between them."
"It is useful for handling large amounts of data. It is very useful for scientific purposes."
"Apache Spark can do large volume interactive data analysis."
"This solution provides a clear and convenient syntax for our analytical tasks."
"It's easy to prepare parallelism in Spark, run the solution with specific parameters, and get good performance."
"VPC itself is pretty good, but understanding it well is key. One of the challenges for beginners is understanding IP address ranges and subnet concepts."
"The tool needs to improve its stability and support which should be faster. The product's pricing is also expensive. When we scale up, we have to pay more."
"You should be able to toggle off some cloud services when you don't need them and switch them on when necessary."
"The solution needs to add step-by-step tutorials for its services."
"There are some differences in the route tables between public and private subnets, which is something that is not properly documented."
"The solution could improve its price."
"If something needs to be highlighted, peering must be maintained."
"Increasing the subnet count could be an improvement."
"The initial setup was not easy."
"We've had problems using a Python process to try to access something in a large volume of data. It crashes if somebody gives me the wrong code because it cannot handle a large volume of data."
"More ML based algorithms should be added to it, to make it algorithmic-rich for developers."
"Apache Spark should add some resource management improvements to the algorithms."
"The solution must improve its performance."
"It should support more programming languages."
"Apache Spark is very difficult to use. It would require a data engineer. It is not available for every engineer today because they need to understand the different concepts of Spark, which is very, very difficult and it is not easy to learn."
"There were some problems related to the product's compatibility with a few Python libraries."
Amazon Virtual Private Cloud is ranked 7th in Compute Service with 32 reviews while Apache Spark is ranked 5th in Compute Service with 60 reviews. Amazon Virtual Private Cloud is rated 9.0, while Apache Spark is rated 8.4. The top reviewer of Amazon Virtual Private Cloud writes "Easy-to-use product with good access control features". On the other hand, the top reviewer of Apache Spark writes "Reliable, able to expand, and handle large amounts of data well". Amazon Virtual Private Cloud is most compared with , whereas Apache Spark is most compared with Spring Boot, AWS Batch, Spark SQL, SAP HANA and Cloudera Distribution for Hadoop. See our Amazon Virtual Private Cloud vs. Apache Spark report.
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We monitor all Compute Service reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
