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New attractive tool, but few under the hood improvements needs to be done.
What do you like best about the product?
GUI is the best and much simpler. It is self explanatory for any range of experience guy to understand.
You need not write complex programming for any kind of implementation. It is as simple as dragging and configuring something you want to implement.
Literally you can connect to any kind of system as a source and any kind of system as a destination.
Scheduling was much more easier when it comes to streamsets, unlike other systems and tools we had, a wide variety of scheduling options here.
Wish there was an option to increase the rate of ingestion.
Having streamsets transfomers is an additional advantage while we are developing the applications.
It is very easy to save and export the jobs or the pipelines. Not just this, it also very easy to share the pipelines/jobs.
Last but not the least, we have topologies where you can view the status of all the pipelines which you have developed and monitor. This can used like a collective system where all the status of the project's jobs can be viewed.
You need not write complex programming for any kind of implementation. It is as simple as dragging and configuring something you want to implement.
Literally you can connect to any kind of system as a source and any kind of system as a destination.
Scheduling was much more easier when it comes to streamsets, unlike other systems and tools we had, a wide variety of scheduling options here.
Wish there was an option to increase the rate of ingestion.
Having streamsets transfomers is an additional advantage while we are developing the applications.
It is very easy to save and export the jobs or the pipelines. Not just this, it also very easy to share the pipelines/jobs.
Last but not the least, we have topologies where you can view the status of all the pipelines which you have developed and monitor. This can used like a collective system where all the status of the project's jobs can be viewed.
What do you dislike about the product?
Debugging an issue will take a lot of time. Logs were not that clear while we were debugging.
You can only select one single source for a pipeline. There are few applications where you need to apply the same logic for multiple sources. For this use case you need to create multiple pipelines and add coordination between them.
You can only select one single source for a pipeline. There are few applications where you need to apply the same logic for multiple sources. For this use case you need to create multiple pipelines and add coordination between them.
What problems is the product solving and how is that benefiting you?
Problems is to trace out the issue while debugging and the benefits is its simplicity to use.
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User friendly interface
What do you like best about the product?
Very easy to use and understand at very first time itself
What do you dislike about the product?
Nothing much but very few minimal things like code suggestions when using scripting languages like groovy,jython and javascript
What problems is the product solving and how is that benefiting you?
Mostly I worked on data movement from different sources to different destinations involving many transformations. Worked on both batch processing and live streaming modes. Worked on triggering events for notifications based on certain conditions.
Recommendations to others considering the product:
I suggest it as one of the best ETL/ELT tool for data ingestion
Experience in using Streamsets in Data Ingestion PipeLine
What do you like best about the product?
Ease of usage including easy to install and configure. Nice GUI interface which is web based for development and admin work. Connectors availability for different systems.
What do you dislike about the product?
Missing auto performance and scalability option. No drifting support. Incase of any issues related to performance and scalability, it is next to impossible to understand what caused the issues and what will be the fix. Also, not useful for ETL operations which makes us to depend upon other tools in E2E integration needs.
What problems is the product solving and how is that benefiting you?
We have used Streamset in our Data Ingestion pipeline for extracting the data sets from various heterogenous source systems like SalesForce, Oracle databases etc. Is very good in extracting the data sets for CRM systems like Salesforce etc but was not able to use it as end to end integration tool as it lacks certain functionalities.
Recommendations to others considering the product:
There few things which StreamSets still lacks and need those to have one stop solution for Data Ingestion.
Lead Data Engineer
What do you like best about the product?
The development speed for a Spark Application.
What do you dislike about the product?
The control hub must be available as part of trail version, with minimal feature
What problems is the product solving and how is that benefiting you?
Convert Spark coding into drag and dropable UI
Recommendations to others considering the product:
If you want to exploit the full power of Apache Spark and maintain it easily then Streamsets in the best way to do it.
Easy to use and very nice interface
What do you like best about the product?
The tool had a lot of options to integrate with different protocols, language and origin. We used this tool to integrate it with Kafka/Aws, send emails and develop different types of data feed. The user interface was quite nice and easy to use. Be it a simple task or a complex task, we were always able to find a processor or executor to achieve our goal.
What do you dislike about the product?
Since the tool was new, there was a limited support on the internet. Ask streamsets page is helpful but I expected a developed ecosystem. Sometimes we faced issue with using known libraries like moment.js. It's a pain to maintain these libraries in your server. We had to use different language to implement certain module because Javascript library for that task was not supported. So our pipelines looked like a bunch of lot of processors each having a different language/framework.
What problems is the product solving and how is that benefiting you?
We were trying to develop data feed for different downstreams originated from wide variety of sources. I really liked how Streamsets control hub had the option to schedule your pipelines. The streamsets control hub had internal version control which was an additional benefit.
It was powerful but lots of jobs failure
What do you like best about the product?
This tool can connect from the ftp or mft server to our MSSQ
What do you dislike about the product?
The jobs designed to our project are usually failing which led our team a lot of monitoring works and manual processing of data.
What problems is the product solving and how is that benefiting you?
It's about a scheduled extracting and storing of data from one server to another. This is very beneficial to our live dashboards which need a real tome update for our clients.
Recommendations to others considering the product:
Maybe, if we can add more real-time support that can cater all time-zones and making the tool more user-friendly.
Been using Streamsets for all of use cases for onprem to cloud transfers
What do you like best about the product?
Easy UX makes it easier to configure pipelines
What do you dislike about the product?
Streamsets Control hub has a lot of issues when multiple DC attached
What problems is the product solving and how is that benefiting you?
Onprem to Cloud data transfers
Managing pipeline over StreamSets on K8S environment
What do you like best about the product?
I did not find any difficulties to integrate streamSet Control Hub with Kubernetes by help of StreamSet Controller Agent.
What do you dislike about the product?
Some time updated docker image of StreamSet agent comes with vulnerabilities which the should take are before release.
What problems is the product solving and how is that benefiting you?
I am managing StreamSet control agent in k8s environment and still did not experienced any issue.
Recommendations to others considering the product:
Yes, i will always recommend the SteamSet to others.
Review on Streamsets
What do you like best about the product?
It is used as real time whenever there are updates in the source database.
What do you dislike about the product?
Sometimes, data sits in Kafka and we need to add extra functionality to pull residual data.
What problems is the product solving and how is that benefiting you?
If we use Streamsets, we can access source data in less than 5 minutes without any further delay.
StreamSets used to be a great open source tool, but has lost it’s niche
What do you like best about the product?
The simplicity of creating data pipelines visually, with no clunky installation and no databases / metadata to manage, like with other ETL tools. All pipeline info is stored on the file system itself.
What do you dislike about the product?
They have closed source their software and locked it behind a SaaS model. This is a relatively recent change which caused lots of headaches
What problems is the product solving and how is that benefiting you?
We are regularly using StreamSets to pull 220 million records daily from Salesforce, eliminating the need to write complicated python code. We are also using this tool for Oracle CDC, which has worked well at scale (20 million transactions / day). I have also used this tool to consume from over 5 different JDBC based sources, with great performance and simple implementation.
The best benefit we have realized is the fact that you can dockerize the SDC service, deploy it in ECS or any container orchestration service, and run pipelines that scale horizontally, instead of having static servers hosting the service. If you can implement this properly, it makes writing ingestion pipelines EXTREMELY simple. I can add a new data source to our ETL jobs within a day, instead of weeks by doing this. And it scales to handle thousands of tables!
The best benefit we have realized is the fact that you can dockerize the SDC service, deploy it in ECS or any container orchestration service, and run pipelines that scale horizontally, instead of having static servers hosting the service. If you can implement this properly, it makes writing ingestion pipelines EXTREMELY simple. I can add a new data source to our ETL jobs within a day, instead of weeks by doing this. And it scales to handle thousands of tables!
Recommendations to others considering the product:
There is no reason not to try the data collector.. It is free to download the Tarbell and install. Try it using docker on your local machine, then deploy it in a development environment for testing.
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