Google Dataflow Competitors and Alternatives

The top Google Dataflow competitors are
  • Apache Spark
  • Apache NiFi
  • AWS Lambda
  • StackStorm
Read reviews of Google Dataflow competitors and alternatives
Abhijit Nayak
Consultant
Manager | Data Science Enthusiast | Management Consultant at a consultancy with 5,001-10,000 employees
Dec 10 2017

What do you think of Apache Spark?

Improvements to My Organization: Organisations can now harness richer data sets and benefit from use cases, which add value to their business functions. • Valuable Features: Distributed in memory processing. Some of the algorithms are resource heavy and executing this requires a lot of RAM and CPU. With Hadoop-related technologies, we can distribute the workload with multiple commodity hardware. • Room for Improvement: Include more machine learning algorithms and the ability to handle streaming of data versus micro batch processing. • Use of Solution: Three to five years. • Stability Issues: At times when users do not know how to use Spark and request a lot of resources, then the underlying JVMs can crash, which is a big sense of worry.  • Scalability Issues: No...
Reviewer39213S
Real User
Chief Executive Officer at a tech services company with 51-200 employees
Jun 05 2018

What is most valuable?

The console is very good, the user experience works very well.

How has it helped my organization?

It has made things a lot easier in terms of restoring if we need to and just not having to worry about the small things.

What needs improvement?

I would like to see some better integration with other providers, like Cohesity, Druva, and others. I also think the Lambda interface could be better.

What other advice do I have?

My most important criteria when selecting a vendor are * user experience * support. I would rate AWS Lambda at a six out of 10 because it's not quite clear that it scales, but it... more»
it_user370506
Real User
Software Engineer at a consultancy with 1,001-5,000 employees
Jun 11 2017

What is most valuable?

We are a research institution and use NiFi for its easy Java extensibility, built-in provenance capturing, and... more»

How has it helped my organization?

We are replacing a custom built Java data ingestion system that over time had become difficult to maintain and was... more»

What needs improvement?

Most of our data is binary and we frequently must write our own processors. Also, there is no support for the stateful... more»

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

It’s free!

Which other solutions did I evaluate?

We previously used custom code and switched to simplify maintenance and improve our functionality.

What other advice do I have?

Think about your data flows as the directed graphs between low-level processing modules, so you can re-use as much of... more»

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