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."This solution is easy to use and especially good at data preparation and wrapping."
"Overall KNIME serves its purpose and does a good job."
"It can handle an unlimited amount of data, which is the advantage of using Knime."
"Valuable features include visual workflow creation, workflow variables (parameterisation), automatic caching of all intermediate data sets in the workflow, scheduling with the server."
"I've tried to utilize KNIME to the fullest extent possible to replace Excel."
"This open-source product can compete with category leaders in ELT software."
"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."
"It's very convenient to write your own algorithms in KNIME. You can write it in Java script or Python transcript."
"I think the most valuable component is that pipelines are built into it and then the feature that you can mirror a cosmos BB for analytics."
"It's quite quick for querying, even with large datasets, and it's scalable. It's also flexible to use, so it's easy to update and get data quickly without wasting time."
"Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same."
"Very interactive and provides flexibility."
"The platform has multiple valuable use cases. They include performance, compatibility, flexibility, and cost."
"What I found most valuable in Microsoft Azure Synapse Analytics is that it's native only for Azure, so you get better performance and there's no issue. To explain further, many different types of data come, in particular, structured and unstructured data. For audit purposes, there's also unstructured data, so the most important aspect is that with Microsoft Azure Synapse Analytics, you have the capability of using both technologies, meaning that you can use or mix structured and unstructured data which is important. This can also be done in Hadoop, and on other platforms, so you have everything in one place. You don't have to worry about how to manage both structured and unstructured data and where to store information. With Microsoft Azure Synapse Analytics, you can take care of everything, particularly in Azure. The solution also provides you with many features apart from analytics, for example, storage which makes it better."
"They are very reliable and cost-effective."
"The MPP (Massively Parallel Processing) architecture helps to make things a lot faster."
"I would prefer to have more connectivity."
"There should be better documentation and the steps should be easier."
"I would like it to have data visualitation capabilities. Today I'm still creating my own data visualtions tools to present my reports."
"The overall user experience feels unpolished. In particular: Data field type conversion is a real hassle, and date fields are a hassle; documentation is pretty poor; user community is average at best."
"The dynamic column name feature could be improved. When attempting to automate processes involving columns, such as with companies, it becomes difficult to achieve the same result when we make changes."
"One thing to consider is that the prebuilt nodes may not always be a perfect fit for your specific needs, although most of the time, they work quite well."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"The configuration for things like high-availability could be more user-friendly for non-technical users."
"The support and price could improve."
"Synapse makes it easy to integrate and onboard data from other Microsoft and Azure sources. The interface is familiar because we were using Azure Data Factory before Synapse. It made the transition even easier because the Synapse interface is exactly the same."
"This is a young product in transition to the cloud and it needs more work before it is both settled as a product and competitive in the market."
"Non-structured data is unavailable with this product."
"The security performance and cost are the two things that needs improvement."
"The filing can be improved."
"I am a researcher. For people to be able to research a solution, there should be at least a free trial. Just advertising a product or saying that this product is better doesn't work. I would strongly recommend providing a lot of free trials and trainings. This will also help Microsoft in having more users or customers. Oracle provides some free trials. You can just go for a free trial and use your database online, which is very good."
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, Oracle Autonomous Data Warehouse and Teradata.
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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!!