We performed a comparison between KNIME and Microsoft Azure Synapse Analytics based on real PeerSpot user reviews.
Find out what your peers are saying about Knime, Weka, IBM and others in Data Mining."We have been able to appreciate the considerable reduction in prototyping time."
"Automation is most valuable. It allows me to automatically download information from different sources, and once I create a workflow, I can apply it anytime I want. So, there is efficiency at the same time."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"It is very fast to develop solutions."
"The most valuable features of KNIME are its ability to convert your sub-workflow into a node. For example, the workflow has many individual native nodes that can be converted into a single node. This representation has simplified my workflow to a great extent. I can present my workflow in a very compact way."
"I've never had any problems with stability."
"The most valuable is the ability to seamlessly connect operators without the need for extensive programming."
"I know I don't use it to its full capacity, but I love the Rule Engine feature. It has allowed me to create lookup tables on the fly and break down text fields into quantifiable data."
"I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use."
"The most valuable feature of Microsoft Azure Synapse Analytics is the capabilities, and the integration with other Azure resources, such as Data Factory, Databricks, and Spark for data processing. The overall ability to compose the solution with other Azure resources is valuable."
"I have not used the technical support from Microsoft Azure Synapse Analytics, but I worked with the developers at Microsoft who were top-notch."
"The stability is pretty good."
"The most valuable feature of Microsoft Azure Synapse Analytics is its integration with the new legacy systems. Whatever application we want to integrate, we receive the reports based on the objects. The solution is easy to purchase from the cloud."
"Azure Synapse combines the strengths of SQL technologies for effective enterprise data management."
"The most valuable aspect of this Microsoft Azure Synapse Analytics is its consolidation of technical support from Microsoft, and its ability to securely host large quantities of data within the cloud environment. The overall ability to manage and maintain Big Data within the cloud provides a heightened level of efficiency, reliability, and support from Microsoft. This results in a superior user experience and an increased level of value for the end user."
"Fills the gap between big data and classic data warehouses."
"The license is quite expensive for us."
"The documentation is lacking and it could be better."
"There are some parameters that I would like to have at a bigger scale. The upper limit of one node that tries to find spots or areas in photos was too small for us. It would need to be bigger."
"The main issue with KNIME is that it sometimes uses too much CPU and RAM when working with large amounts of data."
"From the point of view of the interface, they can do a little bit better."
"Both RapidMiner and KNIME should be made easier to use in the field of deep learning."
"One area that could be improved is increasing awareness and adoption of KNIME among organizations. Despite its capabilities, it is not as well-known as other tools. The advertising and marketing efforts to reach out to companies and universities have not been very successful."
"The visualization functionalities are not good (cannot be compared to, for instance, the possibilities in R)."
"Synapse Analytics' performance slows down if you don't get your distribution right because it gets queued and goes into a single node."
"In the future, Microsoft Azure Synapse Analytics could improve the performance, there are other solutions that are better, such as Databricks."
"It would be beneficial to take the top vendors and identify some kind of straightforward action to work with them. Instead of having to employ a separate vendor tool to be able to move this, it would be nice to be able to go through Microsoft."
"The product needs a tool that allows for work from a laptop instead of a browser."
"One area for improvement could be better integration with Power BI, as well as data integration with BW."
"Could have more connectors and better integration for Hadoop."
"Microsoft Azure Synapse Analytics could improve the section in the solution where you can implement the Python Spark pipelines, it's not the same as in Databricks which would be better."
"Integration with other products is an area that can be improved."
More Microsoft Azure Synapse Analytics Pricing and Cost Advice →
KNIME is ranked 1st in Data Mining with 50 reviews while Microsoft Azure Synapse Analytics is ranked 2nd in Cloud Data Warehouse with 86 reviews. KNIME is rated 8.2, while Microsoft Azure Synapse Analytics is rated 7.8. The top reviewer of KNIME writes "A low-code platform that reduces data mining time by linking script". On the other hand, the top reviewer of Microsoft Azure Synapse Analytics writes "No competitors provide the entire solution to one place ". KNIME is most compared with RapidMiner, Microsoft Power BI, Alteryx and Dataiku, whereas Microsoft Azure Synapse Analytics is most compared with Azure Data Factory, SAP BW4HANA, Snowflake and Oracle Autonomous Data Warehouse.
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I know you're looking for someone who's done research for you but realize that's actually something people get paid to do.
That said, what you're asking about is a mix of quite different tools when you throw KNIME in the mix. I don't know that tool but sounds like its for specific purpose and it's not an Azure tool. Realize there's endless ETL tools out there. I've used about 1/2 dozen in my career. I currently use both ADF and SSIS. I only use ADF when I have to as it's overly complicated to do version management and deal with ARM templates and is very very slow in comparison to SSIS. ADF can however be a good orchestrator for running SSIS - there's an Azure/PaaS version of SSIS called SSIS-IR that can run from ADF. Synapse Analytics pipelines which is actually ADF technology but stripped down. And now there's Fabric Data Factory which is again ADF but even more stripped down. Fabric is also bleeding edge.
ADF has been around for long time now. Anything Azure is cloud based and integrates with Azure services. KNIME is not that. I advise first on understanding fundamental requirements such as, what are the skill levels of your staff with ETL? Are you an Azure shop? What kind of data volumes are you talking about? What sources do you need to connect to (that's a biggy because not all tools talk to all sources!) What are you trying to do - build a datamart or EDW or just copy some data from a source or ? Do you use PowerBI? These will help drive what kind of tool you're looking for. If you want SAAS like as possible tool due to minimal requirements, low data volumes and low staff expertise and starting from scratch, I'd give Fabric a try especially if you want low tech and already into the Power platform. Hope that helps
I believe Synapse is not an ETL tool. ADF is one optional ETL tool for a Synapse Data warehouse.. What Are the Top ETL Tools for Azure Data Warehouse? | Integrate.io
I'd like to step back and pose a bigger option. You see, ETL means making a copy of data you have already. Have you considered a data fabric or mesh, where the data is used where it lies now? Consider this if your data is already used by some systems, but you need to do a more comprehensive analysis of it.
I always want to reduce the replication of databases. The concept of build yet another database to "replace" all the others rarely works out that way. I'd rather beef up the origination system, or use a replica than build a huge portfolio of ETL programs and an army of ops, data governance, and system support to keep them in sync.
Finally, if you really need an ETL tool, i.e. copies of all that data... look for existing talent in your staff. Otherwise, expect to hire some people experienced with the new tool that can advise on design and development and mentor existing staff.
A couple of questions before starting the feature comparison: i. Are you fine with an open-source solution? ii. Any specific reason you have listed ADF? iii. Who will be using these tools and how much learning curve is involved within the team? iv. What kind of data you are dealing with? v. Is data privacy an important factor? vi. Are you looking for only a cloud-based solution or open to a hybrid solution also? vii. What is the maturity level of the team when it comes to working on the cloud ........ These are just a few of the many questions basis which we do self-assessment or measure our preparedness. Let me know if you need more insights. Happy to help!!