IBM StreamSets
IBM SoftwareExternal reviews
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A Powerful Platform for ETL and Streaming Analytics
What do you like best about the product?
The platform’s growing support for automation, reusability, and real-time processing makes it not just an ETL tool, but a full-fledged DataOps platform.
What do you dislike about the product?
IBM Stream Sets is a powerful platform, but it can improve in a few key areas. Handling highly complex or customized integrations can be challenging, and connector support for some newer cloud services could be expanded. The learning curve for Control Hub and CI/CD automation is a bit steep for new users, and error messages during pipeline failures could be more detailed to help with faster troubleshooting.
What problems is the product solving and how is that benefiting you?
Streamsets addressed the challanges associated with managing and integrating diverse data sources in real time. It helps me easy data integration, accurate real time processing and in maintaing data quality through ETL process.
Capable streaming data processing tool
What do you like best about the product?
Listed are the things which I liked most about Streamset -
a. Presence of inbuilt connectors (in-preise version) which can useful in using it for almost every source/target systems.
b. The is GUI is user friendly and it has certainly helped my platform team to create the streaming data pipeline faster )Previously we were using pyspark)
c. Alongwith tool, the Streamset support team is also excellent.
d. The availability of streamsets academy through which we an get our resources trained easily.
a. Presence of inbuilt connectors (in-preise version) which can useful in using it for almost every source/target systems.
b. The is GUI is user friendly and it has certainly helped my platform team to create the streaming data pipeline faster )Previously we were using pyspark)
c. Alongwith tool, the Streamset support team is also excellent.
d. The availability of streamsets academy through which we an get our resources trained easily.
What do you dislike about the product?
There are lesser number of connectors available in the cloud version of Streamsets.
The inability to supports "exactly once" delivery of data creates limitation in few of the use cases.Although we have managed this through workaround but having ths ability in Streamsets will certainly help.
The inability to supports "exactly once" delivery of data creates limitation in few of the use cases.Although we have managed this through workaround but having ths ability in Streamsets will certainly help.
What problems is the product solving and how is that benefiting you?
1.It has allowed us to perform CDC on the mainframe data and put the data to KAFKA topics which can be used by multiple platforms as per their requirement.
2. It has helped to create event based real time pipeline swhich is being used to generate marketing prompts to the customers.
3.The development time (as compared to pyspark) has been reduced as it is low code GUI tool
4. It has also helped in reducing our dependency on other ELT tools e.g. Informatica DEI.
2. It has helped to create event based real time pipeline swhich is being used to generate marketing prompts to the customers.
3.The development time (as compared to pyspark) has been reduced as it is low code GUI tool
4. It has also helped in reducing our dependency on other ELT tools e.g. Informatica DEI.
Streamset make day by day easier
What do you like best about the product?
How quickly a pipeline can be deployed and made to work. On the other hand, the large number of connectors that can be used allows you to connect with almost any data source.
What do you dislike about the product?
In my particular case, I would love for Streamsets to have more direct connections to Google Cloud Platform services, such as stages to be able to directly execute workflows, or cloud functions
What problems is the product solving and how is that benefiting you?
Migrating to Streamsets platform from Streamsets Control Hub really helped us mitigate certain connectivity issues with Control Hub that our DataCollectors were having.
Stream sets - making data engineering simple
What do you like best about the product?
The tool canvas and wasy to use interface. Allows making connectiion with several end points very simple
What do you dislike about the product?
I suppose better diagnosisng support for errors/bugs would have been good
What problems is the product solving and how is that benefiting you?
We often had to use different tools for sourcing data sitting across multiple platforms. Streamsets allows connectivity to various data end points through a single tool. The flexiblity on using any anguage to build engineering workflows makes it very simple
Good Idea, Juvenile Execution
What do you like best about the product?
Nothing - there is not a single upside to using StreamSets. It's expensive, illogical, and rarely works as intended.
What do you dislike about the product?
While there are so many things to dislike about StreamSets, it's randomness and instability are at the top of the list. The only way my team has made StreamSets functional is to rely on it for as little as possible.
What problems is the product solving and how is that benefiting you?
StreamSets creates more problems than it solves. StreamSets has not benefitted me at all.
Service and product improvements
What do you like best about the product?
Open space development and choices on functions. Combination of scripts to enforcing user capabilities.
What do you dislike about the product?
Some GUI Features need to be improved. Need more consideration on user experience.
What problems is the product solving and how is that benefiting you?
Porvided an data ETL environments for data integration.
A great tool to work with Streaming Data
What do you like best about the product?
1. It has got multiple inbuilt components to connect with most of the sources/targets.
2. Its ability to handle & perform transformation on streaming data easily and effectively.
3.Topologies are quite good and provide visibilty on how systems are connected & data flows across enterprise.
4.Orchestration & Scheduling jobs are quite easy.
2. Its ability to handle & perform transformation on streaming data easily and effectively.
3.Topologies are quite good and provide visibilty on how systems are connected & data flows across enterprise.
4.Orchestration & Scheduling jobs are quite easy.
What do you dislike about the product?
1. Debugging is bit difficult, needs slight improvement with the error message.
2. Latency should be reduced as working with large datasets takes a bit of time.
2. Latency should be reduced as working with large datasets takes a bit of time.
What problems is the product solving and how is that benefiting you?
It helped us in collecting & transforming of realtime data so that the same can be used to generate customized messages to the customers.
It has also helped to reduce dependency on costly informatica & Abinitio tools.
It has also helped to reduce dependency on costly informatica & Abinitio tools.
Engineering Manager
What do you like best about the product?
Abstraction of complexity of spark or ETL
What do you dislike about the product?
Scaling capabilities not great
Improve more connectors like DB2, Terradata
Improve more connectors like DB2, Terradata
What problems is the product solving and how is that benefiting you?
ETL
Graphical interface for easier use
What do you like best about the product?
Graphical interface ，make complex ETL process easier.
What do you dislike about the product?
if there is a service can change the query to code automatically
What problems is the product solving and how is that benefiting you?
easy going , and more connection can help me to connect different type of sources
StreamSets data pipelines
What do you like best about the product?
StreamSets has lot of out of box features to use for data pipelines and connect AWS Kinesis, DB or Kafka and send to HDFS & Hive.
What do you dislike about the product?
Some of features like Aerospike connectors has deprecated and MapReduce has issues in control hub running in cluster out of Cloudera.
What problems is the product solving and how is that benefiting you?
Easy integration with big data tools and real time data ingestion.
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