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."One of the greatest advantages of KNIME is that it can be used by those without any coding experience. those with no coding background can use it."
"All of the features related to the ETL are fantastic. That includes the connectors to other programs, databases, and the meta node function."
"It allows for a user-friendly approach where you can simply drag and drop elements to create your model, which is a convenient and effective idea."
"Overall KNIME serves its purpose and does a good job."
"I was able to apply basic algorithms through just dragging and dropping."
"Stability is excellent. I would give it a nine out of ten."
"The product is very easy to understand even for non-analytical stakeholders. Sometimes we provide them with KNIME workflows and teach them how to run it on their own machine."
"Clear view of the data at every step of ETL process enables changing the flow as needed."
"The most valuable feature is performance gains."
"They are very reliable and cost-effective."
"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."
"Data can be stored any way you want in the data warehouse."
"The most advantageous aspect of Microsoft Azure Synapse Analytics is its simplified data transformation process compared to traditional databases. This makes data cleansing and transformation more manageable and straightforward, which we appreciate. It is much easier to build as well."
"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."
"The architecture, including compute and storage, is good."
"Microsoft provides both the platform and the data center, so you don't have to look for a cloud vendor. It saves you from having to deal with two vendors for the same task."
"The documentation needs a proper rework. "
"I would prefer to have more connectivity."
"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."
"It could input more data acquisitions from other sources and it is difficult to combine with Python."
"KNIME can improve by adding more automation tools in the query, similar to UiPath or Blue Prism. It would make the data collection and cleanup duties more versatile."
"The documentation is lacking and it could be better."
"I would like to see better web scraping because every time I tried, it was not up to par, although you can use Python script."
"Not just for KNIME, but generally for software and analyzing data, I would welcome facilities for analyzing different sorts of scale data like Likert scales, Thurstone scales, magnitude ratio scales, and Guttman scales, which I don't use myself."
"It's pay as you go, so you never know what your bill is going to be beforehand, and that's scary for customers. If you have someone who makes a mistake and the program's a loop that is running all night, you could receive a very expensive bill."
"I would like to see them provide the ingestion of images."
"If I'm looking for something good in the cloud, I would want it to have better standard connectors."
"The initial setup is complex."
"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."
"The linked services can be improved. We can create dynamic linked services to access a lot of databases but only those of the same type. For example, I can use the same linked services to access 11 SQL databases. However, if I have 11 SQL databases and five Oracle databases, I need two dynamic linked services. I cannot do it with only one linked service. The UI also needs to be improved. When I have used Azure Synapse for programming with PySpark, Scala, or .NET, for example, the UI has been unstable. If I open two notebooks for programming, one notebook will queue the session of the other."
"From an infrastructure standpoint, I believe it can be more secure in terms of availability."
"I would like to see more ready-to-use products from Synapse. Right now, everything seems a bit futuristic without much modern use."
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!!