

Pentaho Data Integration and Analytics and Rivery compete in the data integration space. Pentaho stands out for its affordability due to its open-source nature, while Rivery is preferred for its automation and ease of deployment, despite its higher cost.
Features: Pentaho Data Integration offers versatile ETL capabilities with drag-and-drop workflows, plugin support, and low-code pipeline creation. Its asynchronous processing can handle complex data tasks efficiently. Rivery provides automated pipelines with built-in integrations, allowing rapid development and minimal coding. Its data quality checks and transformation features enhance data management.
Room for Improvement: Pentaho could improve its interface, expand native connectivity with cloud services, and enhance debugging and documentation. Rivery may benefit from better orchestration features, improved logging, and more competitive pricing for small businesses.
Ease of Deployment and Customer Service: Pentaho supports various deployments, including on-premises and hybrid clouds, but its forum-based customer service varies in effectiveness. Rivery's public cloud model simplifies deployment, offering responsive customer service despite the higher cost, providing a reliable support environment.
Pricing and ROI: Pentaho delivers value with its open-source option, reducing ETL development costs and providing high ROI through efficient project execution. Rivery offers extensive automation features that lower development time, ensuring good ROI, yet its pricing can be challenging for smaller organizations, justified by the automation benefits it provides.
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.
It saved my team time and really reduced manual work, so overall, it improved efficiency.
By using Snowflake and Rivery, I was able to set up and complete project goals myself without the necessity to employ additional data engineers or DevOps.
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
One significant challenge was implementing custom-built Python scripts using Rivery for transformations.
Customer support is great; they are answering really fast.
The customer support for Rivery is excellent.
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.
It has handled growing data volumes and additional pipelines without major issues.
The focus is on the ability to connect to different sources and to put all the data together.
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.
I found the tool very easy to use, allowing me to gain a lot of insights.
The excellent support we received from Rivery team contributes to this perception.
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.
As an end-to-end solution for ETL with Snowflake, Rivery has proven to be reliable and efficient in my day-to-day work.
Agentic AI with open source tools can be used to build all configurations automatically for pipelines.
One feature that stood out in Informatica was the ability to see data flowing through each transformation step while debugging, which I felt was missing in Rivery.
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.
I found myself asking my stakeholder to make it only five times a day because it was really expensive.
I found the pricing and licensing to be fair and competitive compared to other solutions I have seen.
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.
Rivery saved time and money because everything was handled in one place by only one or two data people instead of using the resources of a development team, which is great, and all the knowledge is handled in one team.
The main benefit Rivery brought to my organization was the time we were able to save on development.
Rivery has positively impacted my organization by reducing the need for a big team of data engineers and speeding up the work when we need to connect to a new data source; this can happen really fast.
| Product | Mindshare (%) |
|---|---|
| Pentaho Data Integration and Analytics | 1.7% |
| Rivery | 0.7% |
| Other | 97.6% |

| Company Size | Count |
|---|---|
| Small Business | 18 |
| Midsize Enterprise | 17 |
| Large Enterprise | 32 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 1 |
| Large Enterprise | 3 |
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.
Rivery enhances automation with its built-in pipelines, seamless Snowflake integration, and flexible data management capabilities. It supports extensive connectivity and user-defined functions, aiding efficient data flow management.
Rivery provides a robust platform for automating data ingestion and transformation workflows, integrating effortlessly into data warehouses like Snowflake. Its user-friendly interface and extensive API connectivity simplify data extraction and flow, accommodating diverse needs with custom scripting and user-defined functions. Despite its strengths, improvements are desired in lineage, impact analysis, and advanced visualization, along with better orchestration and logging capabilities. Users also seek price adjustments for smaller organizations and integration with modern AI technologies to elevate analytical capabilities.
What features does Rivery offer?In industries such as retail and finance, Rivery is crucial for managing ETL processes. Retail organizations use it for integrating data from sales channels and customer databases, driving targeted marketing strategies. Finance companies rely on its robust pipelines and Snowflake integration to streamline complex financial data transformations and enhance reporting accuracy.
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