Google Cloud Dataflow Reviews

I primarily work with Google Cloud Dataflow on data analytics use cases, and my experience has been good.

Google Cloud Dataflow is useful for streaming and data pipelines.

There are certain challenges regarding the Google Cloud Composer which can be improved.

I have been working with Google Cloud Dataflow for two years as an implementer.

I rate Google Cloud Dataflow a nine out of ten for stability.

Most of our clients are medium-sized businesses.

I rate Google Cloud Dataflow an eight out of ten for scalability.

I rate Google Cloud Dataflow an eight out of ten for the ease of its initial setup.

Google Cloud Dataflow was deployed in a few hours.

On a scale from one to ten, where one is cheap, and ten is expensive, I rate Google Cloud Dataflow's pricing a four out of ten.

I am using the latest version of Google Cloud Dataflow. I recommend users ensure optimal cloud cost when implementing anything so that cost doesn't increase.

Overall, I rate Google Cloud Dataflow an eight out of ten.

We use the solution as distributed data pipelines. 

I don't need a server running all the time while using the tool. It is also easy to setup. The product offers a pay-as-you-go service. 

When I deploy the product in local errors, a lot of errors pop up which are not always caught. The solution's error logging is bad. It can take a lot of time to debug the errors. It needs to have better logs. 

I have been using the tool since 2018. 

The product is stable. 

I am the single user of the solution. 

The product's setup takes time. You need to setup billing, payments, permissions, accounts, etc. 

The product is worth its money. 

The tool is cheap. 

I would rate the solution an eight out of ten. The product comes with a testing suite. You need to write the test and run it locally and then only deploy it since there are chances of failure. 

We use Google Cloud Dataflow for building data pipelines using Python.

The solution allows us to program in any language we desire. I am familiar with Python, so I chose to use it. However, if someone else wishes to use Java, Spark, or any other language, they can still write the code in Veeam Apache.

It is difficult to comment on areas for improvement for this cloud service since Google is constantly improving and introducing new features. Since I have been using the solution, I have seen many features added to the Apache team data flow, such as data flow notebooks, which were not available in the past.

The technical support has slight room for improvement.

I have been using the solution for two years.

The solution is stable.

The scalability is quite impressive; we can add any number of nodes or instances behind the scenes without any issues from a scalability perspective.

The initial setup is straightforward and easy because it is serverless and only takes a few seconds.

The implementation was completed in-house.

From a cost-saving perspective, I have seen a return on investment with Google Cloud Dataflow.

Google Cloud is slightly cheaper than AWS.

I give the solution an eight out of ten.

The solution is very good for someone who likes the code and who wants to use Spark, a type of programming language, which is Veeam, but the only challenge with this one is we have a learning curve.

we are using Google Cloud Dataflow for retailers and eCommerce.

The most valuable features of Google Cloud Dataflow are the integration, it's very simple if you have the complete stack, which we are using. It is overall very easy to use, user-friendly friendly, and cost-effective if you know how to use it. The solution is very flexible for programmers, if you know how to do scripts or program in Python or any other language, it's extremely easy to use.

Google Cloud Data Flow can improve by having full simple integration with Kafka topics. It's not that complicated, but it could improve a bit. The UI is easy to use but the experience could be better. There are other tools available that do a better job.

I have been using Google Cloud Dataflow for approximately one year.

Google Cloud Dataflow has been around for a while and it is stable.

Google Cloud Dataflow is scalable because it is on the cloud. If we were hosting it we might have some troubles.

We have approximately five people in my organization using the solution. We plan to increase usage but not the engineers that use it.

The technical support is very hard to reach.

The initial setup of Google Cloud Dataflow is simple. The deployment tool is approximately 10 minutes.

I rate the complexity of the initial setup a one out of five.

We did the implementation of Google Cloud Data Flow ourselves. We have five people in our engineering team and one of us that is free does the maintenance of the solution when required. Whoever builds the ETLs and the flow has to build the observability part and monitoring.

We're a startup and we've only recently been building the data architecture and it is too early to tell.

The price of the solution depends on many factors, such as how they pay for tools in the company and its size.

I rate the price of Google Cloud Data Flow a two out of five.

We evaluated other options before choosing Google Cloud Dataflow, such as Confluent. We chose Google Cloud Dataflow because we went towards an all-GCP cloud initiative in the companies. It was more of a position as the stack we were going to use rather than having multiple different components of other third-party companies. 

There are other cool solutions, such as Databricks, but those are for different things. Google Cloud Data Flow is mostly for transformation in the cloud, in streams. There are other nice solutions out there on the market but choosing Google Cloud Data Flow made sense because we have everything integrated into GCP.

I rate Google Cloud Dataflow an eight out of ten.

We use Google Cloud Dataflow for data pipeline and connecting data.

The best feature of Google Cloud Dataflow is its practical connectedness.

I would like Google Cloud Dataflow to be integrated with IT data flow and other related services to make it easier to use as it is a complex tool.

I have been using Google Cloud Dataflow for one and a half years.

Google Cloud Dataflow is a stable solution.

Five people are using Google Cloud Dataflow in our company.

Google Cloud Dataflow is a cheap solution.

I would recommend Google Cloud Dataflow to other users.

Overall, I rate Google Cloud Dataflow an eight out of ten.