Google Dataflow Competitors and Alternatives

Read reviews of Google Dataflow competitors and alternatives
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...
Real User
Chief Executive Officer at a tech services company with 51-200 employees
Jun 05 2018

What do you think of AWS Lambda?

Primary Use Case I back up my MongoDB, that database has user data. The performance of AWS Lambda has been fine. • Improvements to 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. • Valuable Features The console is very good, the user experience works very well. • Room for 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. • Use of Solution One to three years. • Stability Issues I don't have a ton of transactions, so it's very stable from my perspective. But I can imagine that it would not necessarily be as great for an enterprise product. • Scalability Issues ...
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 graphical web interface.

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 brittle. NiFi allows us to organize our ingestion as the directed graphs and provides a useful GUI, that can be used to... 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 operations that require information from other data flows or look-up tables.

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