KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.
$0
Pentaho
Score 5.1 out of 10
N/A
Pentaho is a suite of open source business intelligence and analytics products, now offered and supported by Hitachi Data Systems since the June 2015 acquisition.
N/A
Pricing
KNIME Analytics Platform
Pentaho
Editions & Modules
KNIME Community Hub Personal Plan
$0
KNIME Analytics Platform
$0
KNIME Community Hub Team Plan
€99
per month 3 users
KNIME Business Hub
From €35,000
per year
No answers on this topic
Offerings
Pricing Offerings
KNIME Analytics Platform
Pentaho
Free Trial
No
No
Free/Freemium Version
Yes
No
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
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More Pricing Information
Community Pulse
KNIME Analytics Platform
Pentaho
Considered Both Products
KNIME Analytics Platform
Verified User
Anonymous
Chose KNIME Analytics Platform
Alteryx is a very similar product, almost all the things that are achievable in KNIME Analytics Platform can be done in Alteryx as well, but you have to pay for the Desktop version to conduct the analysis. But with KNIME Analytics Platform it is totally free and can be used …
As a commercial product Alteryx is more polished and can be even easier for a beginner, but KNIME beats Alteryx in functionality and performance. Dataiku takes the integration with Python and Git further than KNIME but isn't at the level of Alteryx and KNIME with its No …
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client …
Our organization also reviewed the Alteryx platform. From our experience KNIME had more functionality, was more stable, responsive, had more features, and was overall a better product from our experience. Alteryx is also a paid product, while KNIME is free.
Alteryx : allows for generally "data" knowledgeable workers to easily implement and develop a data model in an automated fashion. The collaboration tools built in also make is easy for members to share work, best practices, and custom modules
Having used both the Alteryx and [KNIME Analytics] I can definitely feel the ease of using the software of alteryx. The [KNIME Analytics] on the other hand isn't that great but is 90% of what alteryx can do along with how much ease it can do. Having said that, the 90% …
Knime is a more flexible option in some ways, allowing for more data manipulation if you can find the right node. It is not as scaleable in some cases, and some tasks are just easier and faster on SQL databases. It does not build charts or reports as easily as a Tableau and …
Data Scientist - Biotech Data Science Digtialization (BDSD)
Chose KNIME Analytics Platform
KNIME Analytics Platform has a nice visualization comparing to Azure Machine Learning Studio. KNIME also has a good amount of built-in preprocessing nodes and ML training nodes that makes it easier to develop workflow instead of writing codes. However this also limits the …
KNIME is a lower price point and has strong cross platform capabilities. Other platforms are locked to a specific operating system and cost in some cases substantially more, making them less good choices for smaller businesses that still need basic data unification. The fact …
Comparing the KNIME Analytics Platform to Anaconda and MATLAB, KNIME Analytics Platform's upsides are ease of use thanks to graphical interface and intuitiveness, no requirement of programming/coding and pre-existing nodes. Anybody can use it and create models even though …
We need to use SAS/STAT package within SAS to use the advanced statistical functions, but KNIME has inbuilt libraries for the same. Also, the integration with Open source (Python, R, Java codes) allows better scalability & more availability of skilled resources to work upon.
Knime is much more user simple than any high-level programming language. The ability to connect nodes ad produces outputs in minutes is a large benefit for this program
Tableau is having some technical limitations in terms of reporting and integration. But, in the case of Pentaho, it is very effective in terms of cost and also very high user-friendly. I would strongly believe that it will add more value to the organization. That's the reason I …
With Pentaho and its open-source community version, we could start showing the power of the data process and the purpose of a data lake and data warehouse project in the company, without the need for any program language skills in the team or a developer team.
Perhaps Snowflake and SalesForce have some components which align with the Pentaho tools. The Pentaho tools have integrations with these technologies to add more value to the final users. Perhaps the only weakness I can honestly find in the Pentaho tools right now is the lack …
Variety of output of reports and data with clearer and more tangible visual charts. Pentaho has been able to give the user a better sense of visual reporting and a variety of charts. Good features of modules and user-friendliness along with agility and reasonable price and …
I chose Pentaho because it is an open-source and free ETL tool. In addition, JSON and XML-based data migration and conversion operations are very successful. In addition, it works in compliance with all database systems. Finally, we can make ETL packages using the windows Task …
The basic functionality of Pentaho is well matching the capabilities of some of the main competitors. We also selected Pentaho since part of the platform is open source and can be used without commercial licenses. Currently we use a mix of the open source components and the …
Pentaho ranks #3 out of the four. I would always choose Qlik Sense overall since it is so incredibly fast and adaptable. It also has built-in ETL and has a much greater community. If you don't like Qlik, Tableau would be a second choice but the company is difficult to work …
Since the Pentaho platform offers a range of broad functionality across data preparation and advanced analytics, it also can be easily integrated to support many data sources and machine-learning frameworks. Based on that fact, we selected Pentaho to be used in our internal …
In comparison with Excel, that can also work with queries pivots and dashboards, Pentaho offers much more stability from a database point of view, more security options and provides a more stable table, pivots and dashboard designs. We are also completing the business …
We evaluated many typical BI software vendors including Micro-strategy, JasperSoft and Tableau. Tableau would have been a top pick if it had better support for OEM. We had to compete against Tableau in many customers to try to get them to upgrade to use our analytics and found …
I have used Tableau, which also does a great job and has better integration features, but as a report generation/ ETL/ BI tool, I'd recommend Pentaho. I also prefer Pentaho as it is best suited for the current client base that the firm has. It fulfills specific needs with great …
I was not with the company when they selected Pentaho over any other tool. As per my experience, I would recommend Pentaho. One of the reasons are that it is open source. If you know JAVA, you can create your own plugins. I have found its customer support pretty good and quick. …
Pentaho is not as robust or as reputable as Microsoft ETL tools, but it is great for simpler ETL solutions. It has limitations and often lacks the ability for fine-tuning, but it gets the job done and is consistently reliable. Cheaper than other products, it's a great place to …
In terms of price, pentaho seems to be the clear winner for functionality that you get--especially with the community edition. If you don't need to license anything out, even the enterprise edition is fairly reasonably priced. With this in mind, it's a winner in the sense that …
We have done extensive exploration of the BI marketplace but had to eliminate many of the BI vendors due our business model and their licensing model being incompatible or cost prohibitive. We provide reporting to hundreds of clients and hundreds of thousands of end-users and …
Did not have any other products similar to what Pentaho offers out-of-the box for free. The closest was to write some scripts manually so in our case PDI has beat Python scripts.
As previously stated, Pentaho is an excellent tool for start ups and where CTOs are willing to invest in staff training. It may not be user friendly as Tableau or SAS, but once staff master it, development of new solutions becomes limitless.
We have experience with Informatica and Talend. I think that between Talend and Pentaho it's a close fight, although I prefer, personally, Pentaho Kettle (Larger community, more resources). I think that you can say informatica is better than both of them but it is way more …
Pentaho is more powerful than any other reporting tool that is commonly integrated with Odoo. The standard reports are in RML (report modeling language) but Webkit is also available. Both are good for particular types of reports. However, if you want to design a custom report …
We evaluated Panorama, Cognos, MicroSrategy, Jasper Reports, Talend and homegrown solutions. Though each were awesome in their own right, none of them provided a end to end integration like we wanted. Pentaho did the job for us and more. Knowing that Pentaho was built by a team …
Of all the open source tools we looked at Pentaho was the only one with a full suite of tools (i.e. ETL, reporting, dashboards, etc). A lot of the open source tools were either ETL (Talend) or reporting (Jaspersoft).
We used the Pentaho community edition because we were looking for an open source solution. There is a good community involved with Pentaho. I often found Pentaho to be more flexible than Crystal Reports or SSIS but sometimes less polished in the user interface.
Talend and Pentaho have a lot of the same functionality, but Talend's interface is not as intuitive. Talend generates code that is then executed while Pentaho is an engine based tool with highly optimized Java code templates that are compiled at runtime.
Features
KNIME Analytics Platform
Pentaho
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
KNIME Analytics Platform
9.2
Ratings
10% above category average
Pentaho
-
Ratings
Connect to Multiple Data Sources
9.60 Ratings
00 Ratings
Extend Existing Data Sources
10.00 Ratings
00 Ratings
Automatic Data Format Detection
9.10 Ratings
00 Ratings
MDM Integration
7.90 Ratings
00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
KNIME Analytics Platform
8.1
Ratings
4% below category average
Pentaho
-
Ratings
Visualization
8.00 Ratings
00 Ratings
Interactive Data Analysis
8.10 Ratings
00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
KNIME Analytics Platform
8.3
Ratings
2% above category average
Pentaho
-
Ratings
Interactive Data Cleaning and Enrichment
9.00 Ratings
00 Ratings
Data Transformations
9.50 Ratings
00 Ratings
Data Encryption
7.40 Ratings
00 Ratings
Built-in Processors
7.40 Ratings
00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
KNIME Analytics Platform
8.0
Ratings
5% below category average
Pentaho
-
Ratings
Multiple Model Development Languages and Tools
9.50 Ratings
00 Ratings
Automated Machine Learning
8.20 Ratings
00 Ratings
Single platform for multiple model development
9.30 Ratings
00 Ratings
Self-Service Model Delivery
5.00 Ratings
00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
KNIME Analytics Platform
7.3
Ratings
15% below category average
Pentaho
-
Ratings
Flexible Model Publishing Options
8.60 Ratings
00 Ratings
Security, Governance, and Cost Controls
5.90 Ratings
00 Ratings
BI Standard Reporting
Comparison of BI Standard Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Pentaho
9.0
Ratings
10% above category average
Pixel Perfect reports
00 Ratings
8.60 Ratings
Customizable dashboards
00 Ratings
9.90 Ratings
Report Formatting Templates
00 Ratings
8.70 Ratings
Ad-hoc Reporting
Comparison of Ad-hoc Reporting features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Pentaho
8.7
Ratings
8% above category average
Drill-down analysis
00 Ratings
7.60 Ratings
Formatting capabilities
00 Ratings
8.30 Ratings
Integration with R or other statistical packages
00 Ratings
9.30 Ratings
Report sharing and collaboration
00 Ratings
9.70 Ratings
Report Output and Scheduling
Comparison of Report Output and Scheduling features of Product A and Product B
KNIME Analytics Platform
-
Ratings
Pentaho
9.7
Ratings
17% above category average
Publish to Web
00 Ratings
9.60 Ratings
Publish to PDF
00 Ratings
9.80 Ratings
Report Versioning
00 Ratings
9.70 Ratings
Report Delivery Scheduling
00 Ratings
9.90 Ratings
Delivery to Remote Servers
00 Ratings
9.30 Ratings
Data Discovery and Visualization
Comparison of Data Discovery and Visualization features of Product A and Product B
KNIME Analytics Platform has vastly improved our effectiveness when working with large data sets. The self documenting GUI allows analysts to focus on what they are trying to accomplish, not complex code syntax. If we were to use traditional tools, like SQL, work would take much longer and it would be more difficult to collaborate both internally and with clients. Since KNIME Analytics Platform is database oriented, some spreadsheet functions are not supported, which is as it should be. For small data sets we often use Excel vlookup and pivot tables in place of KNIME Analytics Platform. If VBA code is requried, we go to KNIME Analytics Platform as we find VBA to be unstable in Excel.
Pentaho is very well suited to perform data extraction & data mining from various cloud storage & transform that data using various available data models. However, the software struggles when it comes to visualizing the extracted data in an appealing manner & can be difficult for end-users to get an understanding of data tables created using those models.
Visual programming as oppose to scripting encourages data analysts to reap deeper insights from their data
Large community contribution in extending the KNIME Analytics Platform into other areas of analytics, e.g. Text Analytics, Predictive Analytics, ML, etc.
Open source with periodic updates ensures it is equipped to deal with the most sophisticated data analytics use case
Automation - e.g. RapidMiner Studio provides a Turbo Prep function, where one can get to working on models more quickly (RapidMiner is not open source though)
KNIME does not replace a regular reporting tool - it is not meant to. However, if I have already spent some time developing a data acquisition and analytical model, it would be nice to be able to deploy, for example, a monitoring or reporting module that would process data autonomously and react accordingly.
I think the relative obscurity of the tool is a downside, not as many developers, consultants or peers you can tap into.
Lack of a solid user community held us back, looking at Power BI and Qlik, they have huge user communities that help each other out. Would have liked that here.
Smaller company means smaller sales force, and the lack of a local presence made it hard to only interact online with the account rep. Other companies have someone local who often stops by with pre-sales developers to just pitch in free of charge when they have time.
We are happy with Knime product and their support. Knime AP is versatile product and even can execute Python scripts if needed. It also supports R execution as well; however, it is not being used at our end
I will use Pentaho until I find a better tool with a better, easier to use report designer client. For now, Pentaho has been the most powerful reporting tool for our clients because of its ability to connect to Odoo, integrate in Odoo (reports are accessible in Odoo) and the flexibility in report design and parameter integration
The training KNIME Analytics Platform provide helps you get to grips with a product that is already very intuitive. There is a KNIME Analytics Platform way of thinking about addressing problems, but once you understand a couple of patterns which you see again and again in your workflow it all makes sense.
Even if Pentaho requires less technical skills to develop a pipeline or ETL project, its learning curve can be a bit slow since there are many ways to do the same thing as in any other platform. However, in Pentaho, some things can be confusing some moments for non-technical teams.
KNIME's HQ is in Europe, which makes it hard for US companies to get customer service in time and on time. Their customer service also takes on average 1 to 2 weeks to follow up with your request. KNIME's documentation is also helpful but it does not provide you all the answers you need some of the time.
We are an Enterprise customer. They handle problems INSTANTLY when they are critical, including initiation an immediate WebEx screen share call when needed. Smaller/less-critical problems are handled within 1-2 days -- and NEVER fall off their radar, no matter how small. As needed, we can also leverage "professional services" from them -- much of which is included in our Enterprise contract. Finally, when a problem I have discovered turns out to be a bug..they create a JIRA for the fix, and make me a watcher. I love seeing notes come in showing me status updates of bugs filed because of something I found. They really are TOP-NOTCH.
Course Taken: DI1000 Pentaho Data Integration Fundamentals Setup A week before your class started, the instructor will start sending out class material and lab setup instructions. This is helpful so that you understand how the environment is laid out and can start reviewing the content. Ultimately it saved about a 1/2 day trying to setup with 10 other people online which was great! The Course The 3-day course was laid out like many other technical classes with 15-30 minutes instruction and 15-60 minutes of lab exercises. The instructor was very knowledgeable with the functionality from version to version and answered questions as we went along. I was amazed at some of the functionality that was available that I was not using at the time and quickly implemented changes to many existing transformations and jobs. The novice users seemed to catch on quickly and more experienced users explained how some of the functionality was used in their home environments. Towards the end there was enough time so that we were able to ask very directed questions about our own environments. Overall, I really found the class to be informative and deliver enough information to be dangerous. My skills improved and I was able to design better and efficient transformations for the HIE. Course Description: https://training.pentaho.com/instructor-led-training/pentaho-data-integration-fundamentals-di1000
KNIME Analytics Platform is easy to install on any Windows, Mac or Linux machine. The KNIME Server product that is currently being replaced by the KNIME Business Hub comes as multiple layers of software and it took us some time to set up the system right for stability. This was made harder by KNIME staff's deeper expertise in setting up the Server in Linux rather than Windows environment. The KNIME Business Hub promises to have a simpler architecture, although currently there is no visibility of a Windows version of the product.
Get the right people in before starting implementation. Start small and build as you go approach is time consuming and involves lot of rework. Evangalize within the organization the capabilities and limitations equally so that correct delivery expectations are set. Set expectations with the Customer that the tool cannot replace proprietary software in terms of stability/usability and that timelines could change given the new ness of the product.
There are two aspects which put KNIME Analytics Platform ahead of other products. Firstly the fact that KNIME Analytics Platform comes at no cost and no restrictions on its use is an instant winner for any organisation wanting to democratise their data. It means that a client is free to install it on as many machines as they wish without worrying about costs, the number of seats required or payment models or procurement negotiation. It also means that we are not building costs into our clients business. Secondly, KNIME Analytics Platform has a very comprehensive set of tools for importing/exporting data, data manipulation and data science. Some products offer analytics packages on top of their base offering at additional cost and they are still not as comprehensive as what you get with KNIME Analytics Platform for free. For some types of analysis you may require to download additional packages with KNIME Analytics Platform, but its invariably at no cost, those packages are kept out of the main download to keep the size down. Due to the easy integration with R and Python, I view KNIME Analytics Platform as also having the capabilities of those languages too. This has helped me in the past with seamlessly importing a rare filetype and using very specific models not directly available in KNIME Analytics Platform.
Perhaps Snowflake and SalesForce have some components which align with the Pentaho tools. The Pentaho tools have integrations with these technologies to add more value to the final users. Perhaps the only weakness I can honestly find in the Pentaho tools right now is the lack of a powerful web interface for data transformations. There is a web component from which you can access existing data transformations created with the Pentaho Data Integration tool. Still, the web component only allows visualization of the data transformation and remote execution. A complete web interface with remote execution would be excellent, and I'm sure that we might see something like this available at some point in the future.
It is suited for data mining or machine learning work but If we're looking for advanced stat methods such as mixed effects linear/logistics models, that needs to be run through an R node.
Thinking of our peers with an advanced visualization techniques requirement, it is a lagging product.