Microsoft Launches Alteryx Competitor

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Microsoft is launching what at first glance seems like a competitor to Alteryx.

Today, businesses are forced to maintain two types of analytical systems, data warehouses and data lakes. Data warehouses provide critical insights on business health. Data lakes can uncover important signals on customers, products, employees, and processes. Both are critical, yet operate independently of one another, which can lead to uninformed decisions. At the same time, businesses need to unlock insights from all their data to stay competitive and fuel innovation with purpose. Can a single cloud analytics service bridge this gap and enable the agility that businesses demand?

Azure Synapse Analytics
Today, we are announcing Azure Synapse Analytics, a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs.

More from today’s press release: https://azure.microsoft.com/en-us/blog/simply-unmatched-trul…

I just began studying Alteryx recently, like it a lot, and was still trying to figure out the competition when I saw this release.

Was hoping that those who understand Alteryx a bit better could offer some thoughts however. Also, I’m emphatically not stating this is a reason to sell or not hold Alteryx, I just want a clear picture of the competition. Would appreciate any thoughts!

Matt
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If this is the reason for AYX price drop today, it must be another FUD. It’s like the one when Tableau started to offer analytic features. AYX is an analytic tool and is incrementally improved over last two decades. It’s not like some patented technology that can be invented overnight and therefore not easily disrupted.

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Surprised there is not more discussion on this yet given the significant AYX discussion here. From what little I can understand Synapse appears to work well with Azure ML and Power bi and so MS appears to be developing a platform not simply a data visualization tool ( they already have power BI). Don’t know if they can address all the use cases that AYX states. They do talk of data scientists can integrate with python code and also there is code friendly option. They appear to be cloud native though and can handle unlimited data it seems.

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Ayx primarily does business on-prem.

Azure product would be cloud-based.

When you want to do data analytics at scale, cloud is not cheap. The larger g2k, theprimary targetaudience for ayx sales teams, almost always have onprem or hybrid environments.

New startups or smaller companies may get away w cloud-only infrastructure…again…typically not g2k.

So this really isnt an issue today or in next year or so.

I would like ayx to get a better cloud strategy though, for the long term.

Dreamer

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I don’t have any direct knowledge of Alteryx or the MSFT product, but this discussion reminds me of the heyday of 4GLs in the late 80s and early 90s. The idea of a fourth generation language providing very high development productivity was obviously appealing, but for most implementations there was this catch that the most difficult tasks had to be done in C instead of the 4GL. Writing in the 4GL was upwards of 10X more productive than writing in C, but, of course the 80/20 rule applied in both senses. So, the 10X productivity improvement applied to 80% of the code, but it was the 80% that only took 20% of the time so 20% became 2%T where T was the total original time. Meanwhile, 20% of the code that originally took 80% of the time still had to be done in C, so the overall net production was 82%T … an improvement, but not that exciting, really.

Meanwhile, there was one 4GL, the Progress 4GL now known as ABL, in which one could usually write the entire application, so the 10X applied to the whole thing. There were a number of stories at the time about projects started in one of the other 4GLs, running into bottlenecks because of the large amount of C required, getting abandoned 60 or 70% of the way through, and then getting finished ahead of schedule using Progress.

It makes me wonder if there is a parallel here. I.e., the ability to resort to code seems like a plus unless the reality is that the feature is there because one has to resort to code to get the more difficult jobs done. Whereas, if one gets the whole job done in Alteryx without code, that could easily be a significant productivity boost … and a near miracle in maintenance since there is no code to maintain.

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Ayx did touch on cloud a bit in ER CC:

"Derrick Wood

I guess, first for Dean. We’re hearing more analytics software companies partnering and integrating with cloud data lakes and cloud data warehouse vendors like Snowflake, who’s seen a lot of growth. How are you guys positioned around companies like Snowflake? And do you see your users trying to leverage those cloud platforms in their Alteryx workflow?

Dean Stoecker

Yes, and as a matter fact, Derrick, we do. As you know, our design time experience is on-premise and our runtime experience is wherever you choose to put it. We have a fair number of server-based customers who deploy, both in AWS and Azure. Many of them have leveraged Snowflake as their persistence layer of choice. Not all of them. Some have – it’s rare that anyone have a complete set of analytic pipelines that leverage a single data source.

Most of them have many persistence layers, some which resides in cloud vendor of choice, other person are persistence layers reside on-premise. So it’s going to be a hybrid cloud on-prem and ultimately, cloud-to-cloud world for quite some time. We actually have a strong relationship with Snowflake. And many of our customers have moved off of other platforms to go to Snowflake, and we’re quite supportive of our customers who choose to do so."

Dreamer

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First I hear of this so I can’t speak to how viable a competitor this product might be with respect to analytics. But it’s worth keeping in mind that the Alteryx tool suite is far more than just an analytics engines. They have drag and drop functionality for most if not all the precursor operations needed prior to running an analysis of any sort. This is not trivial.

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And this competes w Alteryx in what manner that does not already exist all over the place?

I’d ordinarily go into more detail, but why. If at this point one has not picked up that this has near zero correlation toward the future of Alteryx then why bother.

Hark and Google cane out w a word processor to compete with Word. Less relevant than that.

Tinker

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AYX in the conference call last Thursday note a few important new customer lands. Microsoft was one of them. So MSFT is either starting to use AYX or I suppose that they could have ordered it to study the competition/gold standard.

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And this competes w Alteryx in what manner that does not already exist all over the place?

If at this point one has not picked up that this has near zero correlation toward the future of Alteryx then why bother.

A softer way to say what Tinker is saying is that Microsoft, Google, and/or Amazon compete with pretty much every software business there is. Netflix, Salesforce, Adobe and others have managed to become extremely large companies anyway. Will Alteryx? Only time will tell. But competition from Microsoft will not be the death knell.

Bear

PS - I’m with Tinker so I haven’t even really looked into it, but Brian Withers mentioned on the premium boards: From the video, it seems this [MSFT] product still requires the SQL database “programming” whereas Alteryx doesn’t. Get a TMF subscription (like Rule Breakers) and you can read the whole post: https://discussion.fool.com/4056/could-somebody-help-me-to-deter…

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First I hear of this so I can’t speak to how viable a competitor this product might be with respect to analytics. But it’s worth keeping in mind that the Alteryx tool suite is far more than just an analytics engines. They have drag and drop functionality for most if not all the precursor operations needed prior to running an analysis of any sort. This is not trivial.

When I first got into data analytics and machine learning 5+ years ago this is what you learn, that data always needs massaging before it can be analyzed. And all the books will tell you this takes more of your effort than the actual “learning” does. And I had to do all that in SLQ and in R code. Painful!

I restarted a position in AYX two weeks ago. I’m adding to that position today based on this drop.

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This Databrick press release might be another data point of explaining AYX’s lack of movement post-ER.

https://databricks.com/company/newsroom/press-releases/datab…

Like most on this board I added a lot of AYX in the last month or so (doubling my stake) and I share everyone’s questions about why the stock hasn’t moved up post-ER. Discussions here and in Bert’s writeup seem to have addressed analyst fears of sales growth or billings issues - however after reading this press release I wondered if those analysts might have known a bit more about Databrick’s trajectory and impact.

I’m not a data scientist and can’t speak to Databrick’s relative functionality but at less than half the revenue of AYX, it now sports a slightly higher valuation and looks like something to learn more about.

Databricks appears to be a cloud-first solution. Microsoft is an investor. I have no plans to sell any AYX stock as there is plenty of room in this expanding space, but it’s always nice to better understand the competitive landscape.

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Databricks is interesting. They appear to be more of a comparable to SAS and not Alteryx. They do not mention code free environment or the like. They do not mention cleaning data, that is the most time consuming aspect of the process. They appear to be a tool for more skilled employees and not the “citizen data scientist”.

Their VC valuation is more than $6 billion so they are doing something very right. But it is not a product that enables a business manager to consolidate, clean, analyze, and put into production data insights. It appears to be a product that replaces some of the more expensive, and more difficult to use tools like SAS.

So they are targeting different markets basically.

Tinker

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