Category Archives: Cloud

SaaS Product Power Breakfast with Evan Kaplan of Influx Data

Please join us for tomorrow’s SaaS Product Power Breakfast, Thursday 6/24 at 8am Pacific.  Our guest is veteran technology executive Evan Kaplan, CEO of Influx Data, makers of the open-source, time-series database InfluxDB.

Our theme for tomorrow’s episode is how to manage the transition from traditional open source to true cloud native, something relatively few companies have done, and a transition that Evan has overseen at Influx Data.

We’ll cover questions including:

  • A primer on the traditional open source model
  • What it means to be true cloud native
  • How to approach the transition to true cloud native
  • Perils and pitfalls in the transition
  • Organizational (and people) change in the transition
  • Licensing implications, including protecting the open source from cloud hyperscalers and while trying not to alienate the traditional open source community

Influx Data is a category leader that has raised about $120M from top-tier investors.  Evan has a spectacular background, having been founder/CEO of Aventail for about a decade, CEO of iPass for half a decade, the member of numerous boards, and having serving 5+ years at Influx Data.  I’m super excited to have him on the show.  See you there!

Congratulations to Nuxeo on its Acquisition by Hyland

It feels like the just the other day when I met a passionate French entrepreneur in the bar on the 15th floor of the Hilton Times Square to discuss Nuxeo.  I remember being interested in the space, which I then viewed as next-generation content management (which, by the way, seemed extraordinarily in need of a next generation) and today what we’d call a content services platform (CSP) — in Nuxeo’s case, with a strong digital asset management angle.

I remember being impressed with the guy, Eric Barroca, as well.  If I could check my notebook from that evening, I’m sure I’d see written:  “smart, goes fast, no BS.”  Eric remains one of the few people who — when he interrupts me saying “got it” — that I’m quite sure that he does.

To me, Nuxeo is a tale of technology leadership combined with market focus, teamwork, and leadership.  All to produce a great result.

Congrats to Eric, the entire team, and the key folks I worked with most closely during my tenure on the board:  CMO/CPO Chris McGlaughlin, CFO James Colquhoun, and CTO Thierry Delprat.

Thanks to the board for having me, including Christian Resch and Nishi Somaiya from Goldman Sachs, Michael Elias from Kennet, and Steve King.  It’s been a true pleasure working with you.

Why I’m Advising Cyral

When I sign up to advise a company, I’ll often do a post to let readers know and discuss the reasons why I like the company.  This post is about Cyral, a cloud data security company I’m advising that I’ve been talking with for over a year.

Earlier this year, Cyral announced an $11M series A led by Redpoint, Costanoa, and others.  That was on top of a $4.1M in angel seed financing, bringing the total invested capital to $15.1M.

Cyral_logo_for_web.e28367f0

Cyral does cloud data security.  I indirectly referred to the company in my 2020 Predictions post, where I talked about a new, data-layer approach to security.  Cyral acts as a database proxy on top of every data endpoint in your data layer, watching all the traffic, figuring out (via machine-learning) what is normal, detecting what is not, and either alerting or stopping threats in real-time as they occur.

I remember when I first met co-founder Manav Mital at Peet’s Coffee to discuss the company.  He was surprised that I actually understood a thing or two about databases [1], which was fun. During the meeting a light-bulb went off in my head:  why were data breaches always measured megarows or terarows (hundreds of millions to billions of rows) as opposed say rows or kilorows?  Can’t we stop these things while they’re going down?

I initially viewed Cyral as a next-generation data loss prevention (DLP) company because I thought DLP was about stopping security problems in real-time.  But DLP was more about content than data, more about classification than anomaly detection, and more about business rules than machine learning.  DLP could do things like detect email attachments that contained source code and intercept an outbound email with such an attachment.  It had nothing to do with monitoring traffic to the data endpoints in a company’s both on-premise and (increasingly) cloud data layer, providing visibility into activity, fine-grained data access control, and real-time protection against data exfiltration.  That’s Cyral.

Here are some of the reasons I decided to work with the company.

  • Manav is not only a great guy and (a fellow) member of the illustrious Aster Data mafia [2], he is a second-time entrepreneur, having co-founded Instart Logic, which raised $140M from a top set of investors and built a strong business before eventually hitting hard times in the highly competitive CDN space, ultimately being acquired by Akamai.  It’s great to work with Manav because he has the wisdom from both his successes and his failures on his nearly decade-long journey at Instart.

 

  • I think security is a race without a finish line and thus a great and growing market space.  In addition to data-layer anomaly detection, Cyral provides fine-grained access control in a world where too many applications defeat security using shared data-layer logins.  Cyral can distinguish different users even if they’re coming into the database through the same username/password.  What’s more, Cyral provides more than just security, it provides insight by giving you visibility into who’s doing what.

 

  • New cloud data endpoints from Snowflake to Redshift to Kafka introduce complexity that breaks traditional approaches to security.  The old approach to security was largely about building a strong perimeter.  In a hybrid cloud world, that mixes traditional and cloud data sources, there is no perimeter to defend.  The perimeter is dead, long live data-layer security!

 

When talent meets opportunity, great things can happen.

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Notes

[1] Having worked in technical support at Ingres (RDBMS), as VP of Marketing at Versant (ODBMS), as CMO at BusinessObjects (a BI tool, but with an embedded micro-multidimensional DBMS), as CEO at MarkLogic (XML DBMS), as board member at Aster Data (SQL/MapReduce DBMS), advisor to MongoDB (document-oriented DBMS),  and as CEO of Host Analytics (which included a multidimensional modeling engine) well, heck, you think I might have picked something up.

[2] Aster Data was an amazing well of entrepreneurship and the success of its mafia is an untold story in Silicon Valley.  A large number of companies, some of them amazingly successful, were founded by Aster Data alumni including:  ActionIQ, Arcadia Data, ClearStory, Cohesity, DataHero, Imanis Data, Instart Logic, Level-Up Analytics, Moveworks, Nutanix, The Data Team, ThoughtSpot, and WorkSpan.

 

The New Gartner 2018 Magic Quadrants for Cloud Financial Planning & Analysis and Cloud Financial Close Solutions

If all you’re looking for is the free download link, let’s cut to the chase:  here’s where you can download the new 2018 Gartner Magic Quadrant for Financial Planning and Analysis Solutions and the new 2018 Gartner Magic Quadrant for Cloud Financial Close Solutions.  These MQs are written jointly by John Van Decker and Chris Iervolino (with Chris as primary author on the first and John as primary author on the second).  Both are deep experts in the category with decades of experience.

Overall, I can say that at Host Analytics, we are honored to a leader in both MQs again this year.  We are also honored to be the only cloud pure-play vendor to be a leader in both MQs and we believe that speaks volumes about the depth and breadth of EPM functionality that we bring to the cloud.

So, if all you wanted was the links, thanks for visiting.  If, however, you’re looking for some Kellblog editorial on these MQs, then please continue on.

Whither CPM?
The first thing the astute reader will notice is that the category name, which Gartner formerly referred to as corporate performance management (CPM), and which others often referred to as enterprise performance management (EPM), is entirely missing from these MQs.  That’s no accident.  Gartner decided last fall to move away from CPM as a uber category descriptor in favor of referring more directly to the two related, but pretty different, categories beneath it.  Thus, in the future you won’t be hearing “CPM” from Gartner anymore, though I know that some vendors — including Host Analytics — will continue to use EPM/CPM until we can find a more suitable capstone name for the category.

Personally, I’m in favor of this move for two simple reasons.

  • CPM was a forced, analyst-driven category in the first place, dating back to Howard Dresner’s predictions that financial planning/budgeting would converge with business intelligence.  While Howard published the research that launched a thousand ships in terms of BI and financial planning industry consolidation (e.g., Cognos/Adaytum, BusinessObjects/SRC/Cartesis, Hyperion/Brio), the actual software itself never converged.  CPM never became like CRM — a true convergence of sales force automation (SFA) and contact center.  In each case, the two companies could be put under one roof, but they sold fundamentally different value propositions to very different buyers and thus never came together as one.
  • In accordance with the prior point, few customers actually refer to the category by CPM/EPM.  They say things much more akin to “financial planning” and “consolidation and close management.”  Since I like referring to things in the words that customers use, I am again in favor of this change.

It does, however, create one problem — Gartner has basically punted on trying to name a capstone category to include vendors who sell both financial planning and financial consolidation software.  Since we at Host Analytics think that’s important, and since we believe there are key advantages to buying both from the same vendor, we’d prefer if there were a single, standard capstone term.  If it were easy, I suppose a name would have already emerged [1].

How Not To Use Magic Quadrants
While they are Gartner’s flagship deliverable, magic quadrants (MQs) can generate a lot of confusion.  MQs don’t tell you which vendor is “best” because there is no universal best in any category.  MQs don’t tell you which vendor to pick to solve your problem because different solutions are designed around meeting different requirements.  MQs don’t predict the future of vendors — last-year’s movement vectors rarely predict this year’s positions.  And the folks I know at Gartner generally strongly dislike vector analysis of MQs because they view vendor placement as relative to each other at any moment in time [2].

Many things that customers seem to want from Gartner MQs are actually delivered by Gartner’s Critical Capabilities reports which get less attention because they don’t produce a simple, dramatic 2×2 output, but which are far better suited for determine the suitability of different products to different use-cases.

How To Use A Gartner Magic Quadrant?
In my experience after 25+ in enterprise software, I would use MQs for their overall purpose:  to group vendors into 4 different bucketsleaders, challengers, visionaries, and niche players.  That’s it.  If you want to know who the leaders are in a category, look top right.  If you want to know who the visionaries are, look bottom right.  You want to know which big companies are putting resources into the category but who thus far are lacking strategy/vision, then look top-left at the challengers quadrant.

But should you, in my humble opinion, get particularly excited about millimeter differences on either axes?  No.  Why?  Because what drives those deltas may have little, none, or in fact a counter-correlation to your situation.  In my experience, the analysts pay a lot of attention to the quadrants in which vendors end up in [2] so quadrant-placement, I’d say, is quite closely watched by the analysts.  Dot-placement, while closely watched by vendors, save for dramatic differences, doesn’t change much in the real world.  After all, they are called the magic quadrants, not the magic dots.

All that said, let me wind up with some observations on the MQs themselves.

Quick Thoughts on the 2018 Cloud FP&A Solutions MQ
While the MQs were published at the end of July 2018, they were based on information about the vendors gathered in and largely about 2017.  While there is always some phase-lag between the end of data collection and the publication data, this year it was rather unusually long — meaning that a lot may have changed in the market in the first half of 2018 that customers should be aware of. For that reason, if you’re a Gartner customer and using either the MQs or critical capabilities reports that accompany them, you should probably setup an appointment to call the analysts to ensure you’re working off the latest data.

Here are some of my quick thoughts the Cloud FP&A Solutions magic quadrant:

  • Gartner says the FP&A market is accelerating its shift from on-premises cloud.  I agree.
  • Gartner allows three types of “cloud” vendors into this (and the other) MQ:  cloud-only vendors, on-premise vendors with new built-for-the-cloud solutions, and on-premises vendors who allow their software to be run hosted on a third-party cloud platform.  While I understand their need to be inclusive, I think this is pretty broad — the total cost of ownership, cash flows, and incentives are quite different between pure cloud vendors and hosted on-premises solutions.  Caveat emptor.
  • To qualify for the MQ vendors must support at least two of the four following components of FP&A:  planning/budgeting, integrated financial planning, forecasting/modeling, management/performance reporting.  Thus the MQ is not terribly homogeneous in terms of vendor profile and use-cases.
  • For the second year in a row, (1) Host is a leader in this MQ and (2) is the only cloud pure-play vendor who is a leader in both.  We think this says a lot about the breadth and depth of our product line.
  • Customer references for Host cited ease of use, price, and solution flexibility as top three purchasing criteria.  We think this very much represents our philosophy of complex EPM made easy.

Quick Thoughts on the 2018 Cloud Financial Close Solutions MQ
Here are some of my quick thoughts on the Cloud Financial Close Solutions magic quadrant:

  • Gartner says that in the past two years the financial close market has shifted from mature on-premises to cloud solutions.  I agree.
  • While Gartner again allowed all three types of cloud vendors in this MQ, I believe some of the vendors in this MQ do just-enough, just-cloud-enough business to clear the bar, but are fundamentally still offering on-premise wolves in cloud sheep’s clothing.  Customers should look to things like total cost of ownership, upgrade frequency, and upgrade phase lags in order to flesh out real vs. fake cloud offerings.
  • This MQ is more of a mixed bag than the FP&A MQ or, for that matter, most Gartner MQs.  In general, MQs plot substitutes against each other — each dot on an MQ usually represents a vendor who does basically the same thing.  This is not true for the Cloud Financial Close (CFC) MQ — e.g., Workiva is a disclosure management vendor (and a partner of Host Analytics).  However, they do not offer financial consolidation software, as does say Host Analytics or Oracle.
  • Because the scope of this MQ is broad and both general and specialist vendors are included, customers should either call the Gartner for help (if they are Gartner customers) or just be mindful of the mixing and segmentation — e.g., Floqast (in SMB and MM) and Blackline (in enterprise) both do account reconciliation, but they are naturally segmented by customer size (and both are partners of Host, which does financial consolidation but not account reconciliation).
  • Net:  while I love that the analysts are willing to put different types of close-related, office-of-the-CFO-oriented vendors on the same MQ, it does require more than the usual amount of mindfulness in interpreting it.

Conclusion
Finally, if you want to analyze the source documents yourself, you can use the following link to download both the 2018 Gartner Magic Quadrant for Financial Planning and Analysis and Consolidation and Close Management.

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Notes

[1] For Gartner, this is likely more than a semantic issue.  They are pretty strong believers in a “post-modern” ERP vision which eschews the idea of a monolithic application that includes all services, in favor of using and integrating a series of cloud-based services.  Since we are also huge believers in integrating best-of-breed cloud services, it’s hard for us to take too much issue with that.  So we’ll simply have to clearly articulate the advantages of using Host Planning and Host Consolidations together — from our viewpoint, two best-of-breed cloud services that happen to come from a single vendor.

[2] And not something done against absolute scales where you can track movement over time.  See, for example, the two explicit disclaimers in the FP&A MQ:

Capture

[3] I’m also a believer in a slightly more esoteric theory which says:  given that the Gartner dot-placement algorithm seems to try very hard to layout dots in a 45-degree-tilted football shaped pattern, it is always interesting to examine who, how, and why someone ends up outside that football.

My Appearance on DisrupTV Episode 100

Last week I sat down with interviewers Doug Henschen, Vala Afshar, and a bit of Ray Wang (live from a 777 taxiing en route to Tokyo) to participate in Episode 100 of DisrupTV along with fellow guests DataStax CEO Billy Bosworth and big data / science recruiter Virginia Backaitis.

We covered a full gamut of topics, including:

  • The impact of artificial intelligence (AI) and machine learning (ML) on the enterprise performance management (EPM) market.
  • Why I joined Host Analytics some 5 years ago.
  • What it’s like competing with Oracle … for basically your entire career.
  • What it’s like selling enterprise software both upwind and downwind.
  • How I ended up on the board of Alation and what I like about data catalogs.
  • What I learned working at Salesforce (hint:  shoshin)
  • Other lessons from BusinessObjects, MarkLogic, and even Ingres.

DisrupTV Episode 100, Featuring Dave Kellogg, Billy Bosworth, Virginia Backaitis from Constellation Research on Vimeo.