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."From a user-friendliness perspective, it's a great tool."
"Stability is excellent. I would give it a nine out of ten."
"The visual workflow tools for custom and complex tasks always beat raw coding languages with the agility, speed to deliver, and ease of subsequent changes."
"The solution is good for teaching, since there is no need to code."
"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."
"This solution is easy to use and especially good at data preparation and wrapping."
"The solution allows for sharing model designs and model operations with other data analysts."
"Easy to use, stable, and powerful."
"One central workspace to manage everything for your data warehouse including visualization."
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"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."
"The most important feature for me is the integration with PolyBase."
"Fills the gap between big data and classic data warehouses."
"The integrated workspace in Microsoft Azure Synapse Analytics where everything comes together, such as Power BI and Data Factory, is very good. Additionally, the ability to do dedicated SQL pooling is a benefit."
"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."
"We have found that it is easy to develop and to do the analytics in the modules of data."
"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."
"Compared to the other data tools on the market, the user interface can be improved."
"The solution is inconvenient when it comes to wrangling data that includes multiple steps or features because each step or feature requires its own icon."
"KNIME's licensing and data management aren't as straightforward relative to Alteryx. Alteryx's tools are more sophisticated, so you need fewer to use it compared to KNIME. I think tab implementation could be easier, too."
"There are a lot of tools in the product and it would help if they were grouped into classes where you can select a function, rather than a specific tool."
"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."
"KNIME is not scalable."
"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."
"Microsoft Azure Synapse Analytics could improve its compatibility with Visual Studio. One of the challenges for people moving from an on-premise to a cloud solution, such as Microsoft Azure Synapse Analytics, is that you're constantly working in a browser. There are people that have been working for decades on desktop applications. For them to start working in a browser, it's quite a change. Allowing people to work and do their work inside Visual Studio than in the browser, would be a large advantage."
"Microsoft Azure Synapse Analytics's pricing could be reduced."
"Its stability is an issue. They have been releasing a version every six months to one year, which means that there are many versions available, and clients are not up to speed on the latest one that they're offering. From a stability point of view, they could do better. They're still upgrading their Synapse Analytics workspace, and it is not that stable. Its scalability can also be better."
"The product needs a tool that allows for work from a laptop instead of a browser."
"When I was trying to link services to an SFTP site it was not able to do all the possible encryption that I needed. They can improve by adding more encryption options."
"The solution should offer a serverless model like Snowflake."
"Microsoft Azure Synapse Analytics could improve in usability. I have found the same issue with all Microsoft solutions."
"This solution needs to have query caching so that if the same query is run and the results are available, it will return the data from the cache without having to re-run the query."
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!!