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 can deploy the solution in a cluster as well."
"It provides very fast problem solving and I don't need to do much coding in it. I just drag and drop."
"Easy to connect with every database: We use queries from SQL, Redshift, Oracle."
"Easy to use, stable, and powerful."
"It's a huge tool with machine learning features as well."
"The solution is good for teaching, since there is no need to code."
"What I like the most is that it works almost out of the box with Random Forest and other Forest nodes."
"KNIME is fast and the visualization provides a lot of clarity. It clarifies your thinking because you can see what's going on with your data."
"The solution can scale."
"Azure elasticity allows us to scale as much as we want, and it is pay-as-you-go, so we can scale up as we need to."
"I like the keynotes and their simplicity. Like other Microsoft products, Microsoft Azure Synapse Analytics is simple to understand and use."
"We find the serverless tool to be the most valuable feature ."
"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."
"They are very reliable and cost-effective."
"The solution's scalability is very, very good. It's one of the most important aspects for us."
"Its seamless integration with Azure services is most valuable. If somebody wants to use all Azure services, it is the best solution."
"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."
"The program is not fit for handling very large files or databases (greater than 1GB); it gets too slow and has a tendency to crash easily."
"Though I can use KNIME in a 64-bit platform in the lab, it's missing some features. For example, from my laptop, I can use the image reader feature of KNIME. However, in the lab, the image reader node is missing."
"It's pretty straightforward to understand. So, if you understand what the pipeline is, you can use the drag-and-drop functionality without much training. Doing the same thing in Python requires so much more training. That's why I use KNIME."
"They should look at other vendors like Alteryx that are more user friendly and modern."
"The data visualization part is the area most in need of improvement."
"The most difficult part of the solution revolves around its areas concerning machine learning and deep learning."
"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."
"From an infrastructure standpoint, I believe it can be more secure in terms of availability."
"The support and price could improve."
"I'm not entirely happy with the billing model. I'm not entirely happy with how the enterprise services are pretty expensive, but that's about it."
"Adding more transformations and plugins to the solution is very important."
"Microsoft Azure Synapse Analytics could improve in usability. I have found the same issue with all Microsoft solutions."
"With respect to what needs to be improved, concurrent connectivity has some limitations."
"Synapse Analytics needs to develop an automation framework because now you have to build a cache yourself. You have to build a pipeline in WhereScape, which does end-to-end pipeline automation well. Microsoft should come up with a framework to save people time. If they developed a tool like WhereScape, it would dramatically reduce development time."
"In the future, Microsoft Azure Synapse Analytics has the potential to enhance its capabilities by expanding its connectors, specifically with regard to Oracle solutions, such as operating systems. This would involve a comprehensive approach to adding more connectors for both data input and consumption purposes. By doing so, Microsoft Azure Synapse Analytics would be better equipped to meet the diverse needs of its users and achieve greater efficiency in its performance. The provision of more connectors is definitely a crucial area that needs improvement."
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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!!