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Apache Spark Streaming OverviewUNIXBusinessApplication

Apache Spark Streaming is #10 ranked solution in Streaming Analytics tools. PeerSpot users give Apache Spark Streaming an average rating of 8 out of 10. Apache Spark Streaming is most commonly compared to Amazon Kinesis: Apache Spark Streaming vs Amazon Kinesis. Apache Spark Streaming is popular among the large enterprise segment, accounting for 69% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 24% of all views.
Buyer's Guide

Download the Streaming Analytics Buyer's Guide including reviews and more. Updated: June 2022

What is Apache Spark Streaming?

Spark Streaming makes it easy to build scalable fault-tolerant streaming applications.

Apache Spark Streaming was previously known as Spark Streaming.

Apache Spark Streaming Customers
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
Apache Spark Streaming Video

Apache Spark Streaming Reviews

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Oscar Estorach - PeerSpot reviewer
Chief Data-strategist and Director at theworkshop.es
Real User
Top 5Leaderboard
Mature and stable with good scalability
Pros and Cons
  • "The solution is very stable and reliable."
  • "The solution itself could be easier to use."

What is most valuable?

The solution is very stable and reliable. It's quite mature.  The solution scales very well.

What needs improvement?

The installation is difficult. You definitely need more than one person. That said, if you are implementing the cloud, it's easier. The solution itself could be easier to use. The solution is free to use as it is open-source.

For how long have I used the solution?

I've used the solution for a while. I use it every day. However, it depends on the project.

What do I think about the stability of the solution?

The solution is stable. It's not a new tool. It's quite mature. It's been on the market for many years. We found that especially version 3.0.1 is a good, stable version.
Buyer's Guide
Streaming Analytics
June 2022
Find out what your peers are saying about Apache, Amazon, Microsoft and others in Streaming Analytics. Updated: June 2022.
610,190 professionals have used our research since 2012.

What do I think about the scalability of the solution?

The solution is quite scalable. It is the most scalable tool that I have seen before. We have five people using the solution.

Which solution did I use previously and why did I switch?

I did not previously use a different solution. I've been working in data warehousing for around 20 years ago and I used a batch system that used Oracle Database and is not a scalable system like Spark.

How was the initial setup?

The initial setup is quite involved. Streaming is a huge system. It's different. You need to use another part of the code, however, it's not extremely much. People who work in data need to micro-batch. You need other tools, such as Hadoop or Data Lake, or Kafka to control the data.  It's not easy to install. Not all products are open-source. It is not easy to implement on-premise as you need maybe two technical persons to maintain the system. If you put it in the cloud, it's easier.

What's my experience with pricing, setup cost, and licensing?

It's less expensive to use the cloud. Using on-premises is more costly. Spark is open-source and doesn't actually cost us anything.

What other advice do I have?

It's cheaper for companies to use cloud systems, however, you can implement it on-premise. We use the cloud. As it is the cloud, it's always on the latest version and updates itself regularly. I would rate the product at a nine out of ten. It's very good in terms of its capabilities and I have been very happy with it. I would recommend the solution to other users.

Which deployment model are you using for this solution?

Public Cloud
Disclosure: I am a real user, and this review is based on my own experience and opinions.
Head of Data Science at a energy/utilities company with 10,001+ employees
Real User
Top 5
Open-source, reliable, and enterprise-ready
Pros and Cons
  • "As an open-source solution, using it is basically free."
  • "We would like to have the ability to do arbitrary stateful functions in Python."

What is our primary use case?

We're primarily using the solution for anomaly detection.

What is most valuable?

I like that it's Python. We have a Python ecosystem. Therefore, it fits perfectly.

The initial setup is simple. 

The solution can scale.

It's a stable product.

As an open-source solution, using it is basically free.

What needs improvement?

We would like to have the ability to do arbitrary stateful functions in Python.

For how long have I used the solution?

We started using the solution half a year ago.

What do I think about the stability of the solution?

The solution is stable. There are no bugs or glitches. It doesn't crash or freeze.

What do I think about the scalability of the solution?

It's enterprise-ready. It's very scalable.

As we're using it mostly for data science types of activities, there are maybe eight active users.

How are customer service and support?

While we're purchasing external consulting to support us, the documentation is pretty good.

Which solution did I use previously and why did I switch?

We tried Flink, however, it was not satisfactory.

How was the initial setup?

It's not a complex implementation. In our case, it was easy as we have a hosted environment. The deployment only takes a couple of minutes.

What's my experience with pricing, setup cost, and licensing?

The solution is open-source. That's pretty reasonable. It's basically free.

What other advice do I have?

We are a customer and end-user.

We're using it in Azure, in Databricks. I don't know the exact version of Spark I'm using; it's one of the recent ones.

I would rate the product an eight out of ten.

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Disclosure: I am a real user, and this review is based on my own experience and opinions.
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Buyer's Guide
Streaming Analytics
June 2022
Find out what your peers are saying about Apache, Amazon, Microsoft and others in Streaming Analytics. Updated: June 2022.
610,190 professionals have used our research since 2012.
Chief Innovation & Technology Leader at a mining and metals company with 1,001-5,000 employees
Real User
Top 10
Efficient, better then average, but overly developer-focused

What is our primary use case?

The primary use of the solution is to implement predictive maintenance qualities. 

What is most valuable?

The solution is better than average and some of the valuable features include efficiency and stability.

What needs improvement?

There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused. For example, it is still not plug and play and use as some of the cloud offerings that come ready to use. It is not up there in the reading leading edge.

For how long have I used the solution?

I have been using this solution for approximately one and a half year. 

What do I think about the stability of the solution?

The solution is very stable.

How was the initial setup?

The initial setup is developer-focused but it is not very complex. I can set up a stream in less than an hour. It will stream but It will not be a production-ready stream.

What other advice do I have?

I rate Apache Spark Streaming a six out of ten. 

Which deployment model are you using for this solution?

Public Cloud

If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

Microsoft Azure
Disclosure: I am a real user, and this review is based on my own experience and opinions.