Pentaho Data Integration and Analytics Reviews

Developed ETL processes to load a data warehouse. Has improved our data integration capabilities.

• Easy to use
• Development of the product
• A lot of predefined steps
• Good open source option

There is not a data quality or MDM solution in the Pentaho DI suite.

No issues.

I could not connect to our Hadoop environment in an easy and flexible way, and it was important to scale our data warehouse.

I work with the Community Edition, therefore I do not have support. There was an issue that I could not resolve with community support.

I switched from our previous solution for cost reasons.

It was not complex.

There is a good open source option (Community Edition).

No.

There is a lack of support if you work with the Community Edition.

It's very simple compared to other products out there.

We use Pentaho for data integration, but also PI to implement data mining. That has improved the intelligence behind the data. So, we are able to provide our customer with the ability to understand their data. Our customer produces terabytes of data, so arranging the data, cleaning the data, on data integration, aided our customer to understand the data to improve their business.

One thing that I don't like, just a little, is the backward compatibility. I used Pentaho from version 4, and version 6 does not work with the whole ETL design. So backward compatibility is a problem.

I have worked with this product for seven years.

It's a stable product. In fact, contains some mocks, where you can write your own Java software, and do an ETL, specific for your needs.

The support is very fast, but there are also a lot of forums to address problems, so you can find the solution to your issue easily. There is also the possibility to buy support, and when we bought support they resolved our problem in 24 hours.

It was very, very simple. I copied the integration folder, started the tool to design the ETL, and it worked. Time was required to design the ETL, just to understand how each block works. So, when you understand how each block works, you need spend no more time to use the product.

Before using Pentaho, I analyzed other products to understand what is the best ETL product. I tested Talend and Oracle Data Integrator. Oracle Data Integrator is a little bit more difficult to understand, how it works.

So, I preferred Pentaho Data Integration because you just have to drag and drop the block, draw a line to connect the block, write the query, and connect to the DB. There's nothing else you need to do. For Oracle Data Integrator, and also for Talend, you spend more time installing the product. By contrast, with Pentaho, you just have to copy the folder, launch the product, and then you just need the Java machine and it works.

When you start to use this product, if you have just a little experience and know about ETL, you will have to spend little time to learn the it. The product is very, very simple to understand. You can build functionality by yourself.

Anyone thinking about an ETL product, if they want high productivity on data cleaning and data movement, Pentaho Data Integration, in my opinion, is the best tool.

Data transformation within Pentaho is a nice feature that they have and that I value.

Integration between databases and data import for a BI solution.

I would like to see more improvements with AS400 DB2. I journalled the tables/instance and the data migration is too slow if I compare it with other databases.

There were no issues with the deployment.

Until now, the stability of Pentaho is great. I've already tested various scenarios and I didn't feel a loss of performance.

There have been no issues so far in scaling the product.

I used self-learning to implement it and found that the tool is very easy to understand. For some things, I looked at YouTube videos for conceptual ideas during the planning phase.

I did it myself.

It allows for rapid prototyping of a wide array of ETL workloads.

Support for common Hadoop utilities can be expanded, such as bulk load with composite row keys for HBase, and include drivers for Impala out-of-the-box. A richer interface to Hive could also be beneficial as we currently have to go through a raw connection and execute SQL scripts, for which some syntax is not respected.

As of version 6, there are also some new issues introduced that pose a bit of an annoyance:

1) On kettle's ramp up - log4j errors

2) IBM Websphere MQ Producer - variable substitution for the URL does not work - you have to hardcode.

3) shared.xml for DB connections - variable substitution for connection properties does not work - have to hardcode things like Kerberos principal for a Hive/Impala connection.

We had no issues deploying it.

The robustness of this solution in a production cluster (>30 nodes) remains to be seen.

It is extremely flexible, it allows you to use variables/parameters for just about everything. 

It enables us to automate our reporting and ETL to a very high extent.

The product itself is great, the biggest downside in my opinion is that it is hard to find (hire) people with expertise. Our experience with Pentaho software is that few people have the required expertise. Hiring additional resources for projects can be tough.

Our solution is that we tend to train our own people, it’s definitely not hard to learn, basically anyone with SQL knowledge and experience in another tool can learn using Pentaho Data Integration very easily, but you might end up training them yourselves.

We had no issues with the deployment.

There was no issues with the stability.

We had no issues scaling it for our needs.

Train your own people!

It's an ETL Platform including Big Data enablement. It's the most easy to use, extend and deploy. It helps to connect to various data sources including all available databases.  

We also use Pentaho Analyzer which is an ad-hoc analytics tool built on Mondrian OLAP server that enables the end user to slice and dice the data in various patterns.

We Implement Pentaho for data warehouses and BI features for our various customers. No software can give as complete functionality for fulfilling end user requirements as Pentaho. As well as this, Pentaho offers a flexible platform which enables us to extend the tool to any of the end user's requirement. 

Another impressive feature is the Big Data implementation/integration is very quick and simple without the need to write any code. This enabled our clients to get maximum ROI with in a short period.

Pentaho Dashboard Designer - needs an improvement on the various features of the Dashboards, since there are CTools available and which help to fulfil the gaps, but it needs developers involvement. A full fledged Dashboard designer to perform all the functions of what we do in CDE/CDF would be a great improvement for Pentaho.

Build Process - an inbuilt build process would provide an advantage to migrate between DEV-QA-UAT-PROD, currently it is mostly performed manually.

Data Profiling - including data profiling as part of PDI would be a great improvement to the platform and helps customers to save a lot of effort/cost of data quality.

We are Pentaho Service Providers and have implemented more than 130 projects in Pentaho. We are not direct customers of Pentaho but we recommend Pentaho to our clients if it meets their requirements.

We had no issues with the deployment.

There have been no stability issues.

We have not had any issues scaling it for our customers.

It is quick and easy to implement.

Pentaho is available both in Community (Free) and Enterprise Edition (Subscription based) depending upon your budget.

One of the best feature to lookout in this platform is its flexibility in enhancing or adapting to your requirements. Implementation can be very quick, you can enable few dashboards and analytics to your organization in a week's time.

The best benefit of the product is that it is easy to use and to understand.

We have a huge amount of data that needs to be cleaned and made more valuable for our organization. This Data Integration helps us to achieve that goal.

I have used multiple versions of this product. The initial version we were on was v3.2 and we were had multiple issues, but currently don't find any issues as a blocker. In general, it would be good if we could get better performance from this product.

We haven't had any issues with deployment.

We haven't had any issues with stability except for those described in the Areas for Improvement.

We haven't had any issues with scalability.

There are other products out there, but I feel that this is the best one.

The most valuable thing for me is that it enables a technical product manager to be able to write ETL jobs themselves, which saves developers time so that they can do more important things.

Now developers focus on improving it as a tool (since it's open source) and teach Project Managers about it. The Project Managers are the ones responsible for their own ETL jobs as they know what they want, so hence it's best for them to manage their own jobs.

Its performance can be improved so it will work better with Big Data. Also, sometimes it can be very buggy which keeps away some potential users.

I've used it for two years.

We have had no issues with the deployment.

The performance for Big Data needs to be improved.

We have had no issues scaling it for our needs.

There is a community that can support limited technical help. I'll give a 6 to the community since it's not very active.

It was already in place when I joined the company.

It's very easy to install.

We did it in-hous. It's worth it to have someone in your company who knows Pentaho really well.

ROI is pretty good since it is kind of a major thing in our company.

The only cost is the time it takes for the developer to get to know it.

If your ETL jobs are small and straightforward, then this solution is definitely worth it.