

Pentaho Data Integration and StreamSets are leading solutions competing in the data integration and analytics field. Pentaho is highly regarded for its extensive database connectivity and big data support, while StreamSets is preferred for its simplicity in building pipelines and handling data drift.
Features: Pentaho Data Integration offers extensive database connectivity, a graphical interface for ease of use, and excellent support for data transformation and big data technologies. StreamSets stands out for its user-friendly interface, ease of building pipelines without extensive coding, and robust capabilities for handling data drift and change data capture.
Room for Improvement: Pentaho users highlight limitations in performance with big data, outdated scheduling tools, and a less user-friendly interface lacking enterprise support in the community version. StreamSets could improve its pipeline visualization, error logging, and offer more flexible pricing and better security features.
Ease of Deployment and Customer Service: Pentaho is easily deployable in on-premise environments but faces scalability challenges in the cloud, with users relying heavily on community forums for support. StreamSets excels with flexible deployment options across on-premise, cloud, and hybrid environments, and is praised for its professional support and problem-solving capabilities.
Pricing and ROI: Pentaho's open-source community edition provides notable cost savings, making it attractive to budget-conscious users, while its enterprise edition is more costly. StreamSets offers a free version but its paid model can be expensive for smaller businesses. Larger enterprises find it offers a good ROI due to improved data processing times and resource savings, despite higher costs.
I have seen a return on investment; my team was able to stay extremely small even though we had a lot of data integrations with many companies.
I can testify to the return on investment with metrics regarding time saved; we have increased our efficiency by about 20 to 30 percent due to the swift migration processes facilitated by the tool.
I have noticed a return on investment with Pentaho Data Integration and Analytics in terms of time savings and staff reduction.
24/7 assistance is available for the Enterprise Edition.
take the time to understand our business requirements, offering appropriate recommendations.
Communication with the vendor is challenging
IBM technical support sometimes transfers tickets between different teams due to shift changes, which can be frustrating.
It can be scaled well until you reach a point where you need to perform a lot of operations, and the issue arises when it runs out of memory to handle some data.
Its ability to scale horizontally in cloud-native architectures or for massive real-time processing is limited.
Pentaho Data Integration handles larger datasets better.
Performance issues arise due to reliance on a flowchart-based mechanism instead of scripts, which can lead to longer execution times.
I find that version 3.1 is the most stable version I have ever used.
It's pretty stable, however, it struggles when dealing with smaller amounts of data.
We should also explore more effective partitioning for parallel processing and fine-tuning database connections to reduce load times and improve ETL speed.
Pentaho Data Integration and Analytics can be improved by working with different environments, specifically the possibility to change the variables, meaning I write my variables only once and can change them for different environments such as production or development.
Pentaho Data Integration and Analytics could have real-time processing and automatic alerting, having alerts or automatic notifications when a job fails or when certain data doesn't meet certain rules.
It would be beneficial if StreamSets addressed any potential memory leak issues to prevent unnecessary upgrades.
I use the community version of Pentaho Data Integration and Analytics, and I do not need additional costs.
The setup cost was minimal, and the pricing experience was pretty good.
The company covered it and they had no problem paying for it because they saw that it was cost-effective in terms of performance afterwards.
Pentaho Data Integration and Analytics has positively impacted my organization because it meant we didn't have to write a lot of custom API back-end processing logic; it did the majority of that heavy lifting for us.
It automates the data workflow, including extraction, cleansing, and loading into warehouses for BI reporting purposes, while also removing duplicates, validating data, and standardizing formats, enabling real-time decision-making.
Pentaho Data Integration and Analytics has positively impacted my organization because it is easier to use, and my knowledge about this work facilitates the translation from the source to my final system.
It allows a hybrid installation approach, rather than being completely cloud-based or on-premises.
| Product | Mindshare (%) |
|---|---|
| Pentaho Data Integration and Analytics | 1.7% |
| StreamSets | 1.2% |
| Other | 97.1% |

| Company Size | Count |
|---|---|
| Small Business | 18 |
| Midsize Enterprise | 17 |
| Large Enterprise | 31 |
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 2 |
| Large Enterprise | 11 |
Pentaho Data Integration and Analytics offers an intuitive platform for data workflows, enabling users to easily manage ETL processes across diverse data formats, ensuring seamless automation and development.
With its drag-and-drop interface, Pentaho allows for efficient ETL workflows without extensive coding. It supports a multitude of data formats and sources such as SQL, NoSQL, Hadoop, CSV, and JSON. Advanced features like metadata injection and API integration enable seamless automation. However, improvements in big data performance, better cloud service integration, and enhanced real-time processing capabilities can enhance user experience. Additional connectors and improved documentation are sought after by many. Providing support for more programming languages and optimizing memory usage also presents opportunities for enhancement.
What are the key features of Pentaho Data Integration and Analytics?Pentaho is employed across finance, healthcare, and retail industries for ETL processes. It's instrumental in integrating data from ERP, SAP systems, Excel, and APIs to develop comprehensive reports and data models. Companies rely on its capabilities for both on-premises and cloud deployments, improving data transparency and management.
StreamSets streamlines data pipeline creation, connecting data from multiple sources to destinations like cloud platforms with minimal coding. Its centralized platform and intuitive design enhance ETL and data migration processes.
StreamSets integrates seamlessly with analytics platforms, offering tools such as Data Collector and Control Hub to facilitate data ingestion, transformation, and machine learning integrations. Its user-friendly interface and ready connectors aid in configuring complex data pipelines. With built-in data drift resilience and scheduling options, users experience efficient, scalable data management, despite challenges like latency in cloud storage and interface enhancement needs. Users often employ StreamSets for batch loading, real-time data processing, and smart data pipeline management, offering comprehensive data integration solutions.
What are the key features of StreamSets?In industries like finance and technology, StreamSets supports data migration, machine learning integrations, and analytics by simplifying data transformation and enhancing decision-making capabilities through its robust pipeline management.
We monitor all Data Integration reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.