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Apache Spark Valuable Features

Kürşat Kurt - PeerSpot reviewer
Software Architect at Akbank

AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI. 

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RV
Director at Nihil Solutions

The memory processing engine is the solution's most valuable aspect. It processes everything extremely fast, and it's in the cluster itself. It acts as a memory engine and is very effective in processing data correctly.

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AR
Manager - Data Science Competency at a tech services company with 201-500 employees

One of the key features is that Apache Spark is a distributed computing framework. You can have multiple slaves and distribute the workload between them.

Another feature is memory-based computing. This is unlike Hadoop, which relies on storage. As it uses in-memory data processing, Spark is very fast.

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Buyer's Guide
Apache Spark
June 2022
Learn what your peers think about Apache Spark. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
608,010 professionals have used our research since 2012.
Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at theworkshop.es

Overall, it's a very nice tool.

It is great for transforming data and doing micro-streamings or micro-batching.

The product offers an open-source version.

The solution has been very stable.

The scalability is good.

Apache Spark is a huge tool. It has many use cases and is very flexible. You can use it with so many other platforms. 

Spark, as a tool, is easy to work with as you can work with Python, Scala, and Java.

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NitinKumar - PeerSpot reviewer
Director of Enginnering at Sigmoid

Its scalability and speed are very valuable. You can scale it a lot. It is a great technology for big data. It is definitely better than a lot of earlier warehouse or pipeline solutions, such as Informatica.

Spark SQL is very compliant with normal SQL that we have been using over the years. This makes it easy to code in Spark. It is just like using normal SQL. You can use the APIs of Spark or you can directly write SQL code and run it. This is something that I feel is useful in Spark.

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SS
Co-Founder at a tech vendor with 11-50 employees

Apache Spark can do large volume interactive data analysis.

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AmitMataghare - PeerSpot reviewer
Associate Director at PwC

One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast.

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PE
Senior Test Automation Consultant / Architect at a tech services company with 11-50 employees

It is useful for handling large amounts of data. It is very useful for scientific purposes.

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Onur Tokat - PeerSpot reviewer
Big Data Engineer Consultant at Collective[i]

The most valuable feature is that Spark uses Scala, which has good data evaluation functions. Spark also supports good distribution on the clusters and provides optimization on the APIs.

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GA
Senior Solutions Architect at a retailer with 10,001+ employees

I like that it can handle multiple tasks parallelly. I also like the automation feature. JavaScript also helps with the parallel streaming of the library.

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Buyer's Guide
Apache Spark
June 2022
Learn what your peers think about Apache Spark. Get advice and tips from experienced pros sharing their opinions. Updated: June 2022.
608,010 professionals have used our research since 2012.