2018-06-27T19:19:00Z
Miriam Tover - PeerSpot reviewer
Service Delivery Manager at PeerSpot (formerly IT Central Station)
  • 1
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What do you like most about Apache Spark?

Hi Everyone,

What do you like most about Apache Spark?

Thanks for sharing your thoughts with the community!

21
PeerSpot user
21 Answers
Ilya Afanasyev - PeerSpot reviewer
Senior Software Development Engineer at Yahoo!
Real User
Top 5Leaderboard
2022-08-03T04:09:48Z
Aug 3, 2022

There's a lot of functionality.

Search for a product comparison
SK
Chief Technology Officer at a tech services company with 11-50 employees
Real User
2022-07-04T15:18:53Z
Jul 4, 2022

The most valuable feature of Apache Spark is its ease of use.

AmitMataghare - PeerSpot reviewer
Associate Director at PwC
Real User
Top 20
2022-04-27T08:19:23Z
Apr 27, 2022

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.

Salvatore Campana - PeerSpot reviewer
CEO & Founder at XAUTOMATA TECHNOLOGY GmbH
Real User
Top 5
2022-04-27T08:19:19Z
Apr 27, 2022

Spark helps us reduce startup time for our customers and gives a very high ROI in the medium term.

Onur Tokat - PeerSpot reviewer
Big Data Engineer Consultant at Collective[i]
Consultant
Top 20
2022-02-15T16:44:00Z
Feb 15, 2022

Spark can handle small to huge data and is suitable for any size of company.

SS
Co-Founder at a tech vendor with 11-50 employees
Real User
Top 5
2021-12-28T09:52:00Z
Dec 28, 2021

Apache Spark can do large volume interactive data analysis.

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Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at theworkshop.es
Real User
Top 5Leaderboard
2021-08-18T14:51:07Z
Aug 18, 2021

The solution has been very stable.

GA
Senior Solutions Architect at a retailer with 10,001+ employees
Real User
2021-03-27T15:39:24Z
Mar 27, 2021

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.

NitinKumar - PeerSpot reviewer
Director of Enginnering at Sigmoid
Real User
Top 5Leaderboard
2021-02-01T12:04:16Z
Feb 1, 2021

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.

Kürşat Kurt - PeerSpot reviewer
Software Architect at Akbank
Real User
2020-10-28T02:27:29Z
Oct 28, 2020

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.

RV
Director at Nihil Solutions
Real User
2020-07-23T07:58:35Z
Jul 23, 2020

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.

Gopi Krishnan - PeerSpot reviewer
User at Ideas2IT Technologies
Real User
2020-06-10T05:27:31Z
Jun 10, 2020

I love every core functionality of Apache Spark Initially they have only provided RDD basic interface to process the data across distributed cluster. Then it evolved to dataframe and dataset interface with optimised execution engine and more flexibility for developers to perform querying on the data.

KamleshKhollam - PeerSpot reviewer
Managing Consultant at a computer software company with 501-1,000 employees
Real User
Top 20
2020-02-02T10:42:14Z
Feb 2, 2020

The processing time is very much improved over the data warehouse solution that we were using.

it_user1223676 - PeerSpot reviewer
Lead Consultant at a tech services company with 51-200 employees
Consultant
2020-01-29T11:22:00Z
Jan 29, 2020

The main feature that we find valuable is that it is very fast.

SS
Co-Founder at a tech vendor with 11-50 employees
Real User
Top 5
2020-01-29T11:22:00Z
Jan 29, 2020

The features we find most valuable are the machine learning, data learning, and Spark Analytics.

SA
Technical Consultant at a tech services company with 1-10 employees
Consultant
2019-12-23T07:05:00Z
Dec 23, 2019

I feel the streaming is its best feature.

Mohamed Ghorbel - PeerSpot reviewer
Director of BigData Offer at IVIDATA
Real User
2019-12-09T10:58:00Z
Dec 9, 2019

The solution is very stable.

AD
Senior Consultant & Training at a tech services company with 51-200 employees
Consultant
2019-10-13T05:48:00Z
Oct 13, 2019

The most valuable feature of this solution is its capacity for processing large amounts of data.

LC
Snr Security Engineer at Securonix Solutions
Real User
2019-07-14T10:21:00Z
Jul 14, 2019

The scalability has been the most valuable aspect of the solution.

it_user946074 - PeerSpot reviewer
Principal Architect at a financial services firm with 1,001-5,000 employees
Real User
2019-07-10T12:01:00Z
Jul 10, 2019

I found the solution stable. We haven't had any problems with it.

2018-06-27T19:19:00Z
Jun 27, 2018

Features include machine learning, real time streaming, and data processing.

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I haven't used SQream personally. However, if you are only considering GPU based rdbms's please check the following https://hackernoon.com/which-gpu-database-is-right-for-me-6ceef6a17505
Miriam Tover - PeerSpot reviewer
Service Delivery Manager at PeerSpot (formerly IT Central Station)
Aug 3, 2022
Hi, We all know it's really hard to get good pricing and cost information. Please share what you can so you can help your peers.
2 out of 10 answers
SA
Technical Consultant at a tech services company with 1-10 employees
Dec 23, 2019
I would suggest not to try to do everything at once. Identify the area where you want to solve the problem, start small and expand it incrementally, slowly expand your vision. For example, if I have a problem where I need to do streaming, just focus on the streaming and not on the machine learning that Spark offers. It offers a lot of things but you need to focus on one thing so that you can learn. That is what I have learned from the little experience I have with Spark. You need to focus on your objective and let the tools help you rather than the tools drive the work. That is my advice.
KamleshKhollam - PeerSpot reviewer
Managing Consultant at a computer software company with 501-1,000 employees
Feb 2, 2020
The initial setup is straightforward. It took us around one week to set it up, and then the requirements and creation of the project flow and design needed to be done. The design stage took three to four weeks, so in total, it required between four and five weeks to set up.
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