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IBM StreamSets

Score8.2 out of 10

8 Reviews and Ratings

What is IBM StreamSets?

IBM® StreamSets enables users to create and manage smart streaming data pipelines through a graphical interface, facilitating data integration across hybrid and multicloud environments. IBM StreamSets can support millions of data pipelines for analytics, applications and hybrid integration.

Categories & Use Cases

IBM StreamSets does the job

Use Cases and Deployment Scope

So in my organisation we majorly use IBM StreamSets to automate data flows between our CRM and analytics tools. Before it, we used to do it manually/ some other non effective tool and spend hours moving and cleaning data which was quite frustrating to be honest. Now we can set up pipelines that run quite smoothly and also keeps the reports accurate.

Pros

  • It makes building data pipelines quite super intuitive even for non coders.
  • Ir also handles real time data ingestion effortlessly so I always have up to date information for my reports.
  • It's great at monitoring data quality as well.

Cons

  • The error messages I feel aren t always very descriptive so troubleshooting can take longer
  • Maybe more customisation options for scheduling can be done, rest it works pretty well.

Return on Investment

  • Reduced manual handling, cutting down operational costs for our team.
  • It also accelerated our time to Insight, which has eventually led to faster decision making.
  • Data quality is improved.

Usability

Other Software Used

Snowflake, IBM Planning Analytics

Helpful alerts for monitoring and errors

Use Cases and Deployment Scope

I use IBM StreamSets for AI-related tasks including continuously training models, as well as for real-time data streaming, handling schema changes, and simply scaling pipelines.

Pros

  • it connects to many data sources and helps catch issues early with built-in alerts and monitoring tools
  • it supports real-time and batch processing, handles data drift well, and makes pipeline debugging easier with the updated UI

Cons

  • it lag when handling large amounts of data
  • the error logs were sometimes difficult to interpret
  • support took time to respond when I needed urgent help

Return on Investment

  • it reduced the time I spent managing and updating pipelines when data formats changed
  • it saved us from building everything from scratch by making data movement between systems easier
  • it helps scale workflows as data volume grows, without much extra effort

Usability

Other Software Used

Teamcenter, Vena, Miro

Real-Time Data Pipelines Made Simple with IBM StreamSets

Use Cases and Deployment Scope

I mainly use IBM StreamSets to stream data from our on-prem systems to cloud applications and use them in real-time user applications to give them the latest information of various business reports that users create on different systems like client onboarding applications etc which then gets streamed to advisor applications where the advisor users create reports out of this available data and use it in their regular day to day work activities.

Pros

  • It helps streaming huge data that we have in our Teradata database to various reporting applications that runs on cloud seamlessly.
  • We also use IBM StreamSets to power few BI dashboards that our product managers use on regular basis to showcase various data with clients.
  • I think the data quality is way better compared to Informatica tool.

Cons

  • IBM should make things easy for beginners to get started with IBM StreamSets tool. Most new joinees in my team always find it difficult to do debugging in existing pipelines that we have.
  • The integration limitations are there. Like compared to Java where it integrates well but other frameworks like Python, .NET etc, the support is not so good.
  • The UI/UX interface, while intuitive for simple pipelines, sometime becomes cluttered and hard to navigate when managing complex pipelines involving more data streams.

Return on Investment

  • With IBM StreamSets we are able to do realtime data integration from our data warehouse to various user facing applications in cloud without much overheads.
  • Also, the low code pipeline design and reusable templates helps me create more pipelines at faster pace and make things prod ready in short time.
  • One negative thing that I can say is the licensing cost. Initially when we started using we had very less data pipeline so our usage was very minimal during the POC stage. Later when we started creating pipelines, we started seeing the licensing cost go up huge. So this is the only negative thing I feel.

Usability

Alternatives Considered

Informatica Cloud API & App Integration

Other Software Used

Snowflake, Liquibase, Denodo

IBM StreamSets - Build it and Watch it Run.

Use Cases and Deployment Scope

We use IBM StreamSets for batch loading of data sets between disparate applications into a Data estate so we can query the data to find patterns. We also use IBM StreamSets to handle our continuously streaming data requirements. We went with IBM StreamSets over the competition because of their unique (patented) architecture.

Pros

  • Real-Time Data Ingestion.
  • Streaming Pipelines at Scale.
  • Handling Data Drift and Schema Changes.
  • Flexibility Across Hybrid/Multi-Cloud/On-Prem Environments.

Cons

  • Performance handling Large Data Volumes.
  • Debugging, Error Logging, and Observability.
  • Connector/Integration Coverage.

Return on Investment

  • Huge reduction in maintenance as the StreamSets pipelines are resilient.
  • Eliminated the need for other data ingestion tools, saving us hundreds of thousands annually.

Usability

Alternatives Considered

Datadog, Fivetran and SnapLogic

Other Software Used

Salesforce Lightning Platform, Snowflake

IBM StreamSets the data giant

Use Cases and Deployment Scope

I used IBM StreamSets for data analysis. It is a brilliant tool for monitoring data for analysis and provide pie charts and graphs in an easily readable format which lets even a not so well trained but knows enough person it read it efficiently and accurately. The charts and graphs give thorough information about the data without missing any key points.

Pros

  • Graphs and charts are designed well
  • Data summation is amazing
  • Easy to read and understand the summed up information

Cons

  • Where the person's skillsets in data analysis is not of an expert.
  • Data monitoring and analysis.
  • Customer data for better customer acquisition

Return on Investment

  • Good for the Analysis and the product team to decide what to work on next. So, we have a better video watch time.
  • What are the pages, sections of the websites that are less touched, so they can be changed or removed altogether to save company's money.
  • What are the areas we need to improve on, on the basis of categories and sub-categories that are less watched.

Usability

Alternatives Considered

Fivetran, AWS Glue and Informatica PowerCenter (legacy)

Other Software Used

IBM API Connect, TemplateToaster, AWS Chatbot