25 posts categorized "LucidWorks"

June 28, 2017

Poor data quality gives search a bad rap

If you’re involved in managing the enterprise search instance at your company, there’s a good chance that you’ve experienced at least some users complain about the poor results they see. 

The common lament search teams hear is “Why didn’t we use Google?” when in fact, sites that implemented the GSA but don’t utilize the Google logo and look, we’ve seen the same complaints.

We're often asked to come in and recommend a solution. Sometimes the problem is simply using the wrong search platform: not every platform handles every user case and requirement equally well. Occasionally, the problem is a poorly or misconfigured search, or simply an instance that hasn’t been managed properly. Even the renowned Google public search engine doesn’t happen by itself, but even that is a poor example: in recent years, the Google search has become less of a search platform and more of a big data analytics engine.

Over the years, we’ve been helping clients select, implement, and manage Intranet search. In my opinion, the problem with search is elsewhere: Poor data quality. 

Enterprise data isn’t created with search in mind. There is little incentive for content authors to attach quality metadata in the properties fields of Adobe PDF Maker, Microsoft Office, and other document publishing tools. To make matters worse, there may be several versions of a given document as it goes through creation, editing, reviews, and updates. And often the early drafts, as well as the final version, are in the same directory or file share. Very rarely does a public facing web site content have such issues.

Sometimes content management systems make it easy to implement what is really ‘search engine optimization’ or SEO; but it seems all too often that the optimization is left to the enterprise search platform to work out.

We have an updated two-part series on data quality and search, starting here. We hope you find it helpful; let us know if you have any questions!

June 22, 2017

First Impressions on the new Forrester Wave

The new Forrester Wave™: Cognitive Search And Knowledge Discovery Solutions is out, and once again I think Forrester, along with Gartner and others, miss the mark on the real enterprise search market. 

In the belief that sharing my quick first impression will at least start a conversation going until I can write up a more complete analysis, I am going to share these first thoughts.

First, I am not wild about the new buzzterms 'cognitive search' and "insight engines". Yes, enterprise search can be intelligent, but it's not cognitive. which Webster defines as "of, relating to, or involving conscious mental activities (such as thinking, understanding, learning, and remembering)". HAL 9000 was cognitive software; "Did you mean" and "You might also like" are not cognition.  And enterprise search has always provided insights into content, so why the new 'insight engines'? 

Moving on, I agree with Forrester that Attivio, Coveo and Sinequa are among the leaders. Honestly, I wish Coveo was fully multi-platform, but they do have an outstanding cloud offering that in my mind addresses much of the issue.

However, unlike Forrester, I believe Lucidworks Fusion belongs right up there with the leaders. Fusion starts with a strong open source Solr-based core; an integrated administrative UI; a great search UI builder (with the recent acquisition of Twigkit); and multiple-platform support. (Yep, I worked there a few years ago, but well before the current product was created).

I count IDOL in with the 'Old Guard' along with Endeca, Vivisimo (‘Watson’) and perhaps others - former leaders still available, but offered by non-search companies, or removed from traditional enterprise search (Watson). And it will be interesting to see if Idol and its new parent, Microfocus, survive the recent shotgun wedding. 

Tier 2, great search but not quite “full” enterprise search, includes Elastic (which I believe is in the enviable position as *the* platform for IoT), Mark Logic, and perhaps one or two more.

And there are several newer or perhaps less-well known search offerings like Algolia, Funnelback, Swiftype, Yippy and more. Don’t hold their size and/or youth against them; they’re quite good products.

No, I’d say the Forrester report is limited, and honestly a bit out of touch with the real enterprise search market. I know, I know; How do I really feel? Stay tuned, I've got more to say coming soon. What do you think? Leave a comment below!

January 25, 2017

Lucidworks 3 Released!

Today Lucidworks announced the release Fusion 3, packed with some very powerful capabilities that, in many ways, sets a new standard in functionality and usability for enterprise search.

Fusion is tightly integrated Solr 6, the newest version of the popular, powerful and well-respected open source search platform. But the capabilities that really set Fusion 3 apart are the tools provided by Lucidworks on top of Solr to reduce the time-to-productivity.

It all starts at installation, which features a guided setup to allow staff, who may be not be familiar with enterprise search, to get started quickly and to built quality, full-featured search applications.

Earlier versions of Fusion provided very powerful ‘pipelines’ that allowed users to define a series of custom steps or 'stages' during both indexing and searching. These pipelines allowed users to add custom capabilities, but they generally required some programming and a deep understanding of search.

That knowledge still helps, but Fusion 3 comes with what Lucidworks calls the “Index Workbench” and the “Query Workbench”. These two GUI-driven applications let mere mortals set up capabilities that used to require a developer, and enables developers to create powerful pipelines in much less time.

What can a pipeline do? Let's look at two cases.

On a recent project, our client had a deep, well developed taxonomy, and they wanted to tag each document with the appropriate taxonomy terms. In the Fusion 2.x Index Pipeline, we wrote code to evaluate each document to determine relevant taxonomy terms; and then to insert the appropriate taxonomy terms into the actual document. This meant that at query time, no special effort was required to use the taxonomy terms in the query: they were part of the document.

Another common index time task is to identify and extract key terms, perhaps names and account numbers, to be used as facets.

The Index Workbench in Fusion 3 provides a powerful front-end to these capabilities that have long been part of Fusion; but which are now much easier for mere mortals to use.

The Query Workbench is similar, except that it operates at query time, making it easy to do what we’ve long called “query tuning”. Consider this: not every term a user enters for search is of equal important. The Query Workbench lets a non-programmer tweak relevance using a point-and-click interface. In previous visions of Fusion, and in most search platforms, a developer needed to write code to do the same task.

Another capability in Fusion 3 addresses a problem everyone who has ever installed a search technology has faced: how to insure that the production environment exactly mirrors the dev and QA servers. Doing so was a very detailed and tedious task; and any differences between QA and production could break something.

Fusion 3 has what Lucidworks calls Object Import/Export. This unique capability provides a way to export collection configurations, dashboards, and even pipeline stages and aggregations from a test or QA system; and reliably import those objects to a new production server. This makes it much easier to clone test systems; and more importantly, move search from Dev to QA and into production with high confidence that production exactly matches the test environment.

Fusion 3 also extends the Graphical Administrative User Interface to manage pretty much everything your operations department will need to do with Fusion. Admin UIs are not new; but the Fusion 3 tool sets a new high bar in functionality.

There is one other capability in Fusion 3 enabled by a relatively new capability in Solr: SQL.

I know what you’re thinking: “Why do I want SQL in a full-text application?”

Shift your focus to the other end.

Have you ever wanted to generate a report that shows information about inventory or other content in the search index? Let’s say on your business team needs inventory and product reports on content in your search-driven eCommerce data. The business team has tools they know and love for creating their own reports; but those tools operate on SQL databases.

This kind of reporting has always been tough in search, and typically required some customer programming to create the reports. With the SQL querying capabilities in Solr 6, and security provided by Fusion 3, you may simply need to point your business team at the search index, verify their credentials, and connect via OBDC/JDBC, and their existing tools will work.

What Else?

Fusion 3 is an upgrade from earlier versions, so it includes Spark, an Apache took with built-in modules for streaming, SQL, machine learning and graph processing. It works fine on Solr Cloud, which enables massive indices and query load; noit to mentin failover in the even of hardware problems. 

I expect that Fusion 3 documentation, and the ability to download and evaluate the product, will be on the Lucidworks site today at www.lucidworks.com. “Try it, you’ll like it”.

While we here at New Idea Engineering, a Lucidworks partner, can help you evaluate and implement Fusion 3, I’d also point out that our friends at MC+A, also Lucidworks partners, are hosting a webinar Thursday, January 26th. The link this link to register and attend the webinar: http://bit.ly/2joopQK.

 

Lucidworks CTO Grant Ingersol will be hosting a webinar on Friday, February 1st. Read about it here.

 

/s/ Miles

November 01, 2016

One search to rule them all

(Originally published on LinkedIn)

Lucene was ‘born’ in 1999, created by Doug Cutting; and in 2005, it became a top-level Apache project. That year, Gartner Group announced that the search ‘Leaders’ platforms on their Enterprise Search Magic Quadrant included Autonomy, FAST, Endeca, IBM Omnifind, and Verity. The Google Search Appliance was right on the cusp between ‘Challengers’ and ‘Leaders’. Not many people knew about Lucene; and few who did saw it as much more than a quirky little project.

Just a year later, Yonik Seeley and his employer, CNET Networks, published and donated the Solr search server to the Apache Software Foundation, where it became an incubator project in 2006; the two projects soon merged into a single top-level Apache project. That same year, Gartner narrowed the ‘Leaders’ in their 2006 Magic Quadrant for Search to Autonomy (which acquired Verity the previous year), FAST, and Endeca.

Jump forward to the present. FAST is gone, acquired by Microsoft in 2008 and morphed into SharePoint Search. Hewlett-Packard acquired Autonomy in October of 2011, followed a few weeks later by Oracle’s acquisition of Endeca. Endeca is no longer available as a search platform; and Autonomy is mostly seen as a strategy to keep a large number of HP consultants fully employed, often on compliance applications.

Only a spattering of commercial enterprise search platforms that once flooded the market just a few years back exist any more. While Gartner continues to list 14 or 15 products in their Magic Quadrant Enterprise Search grid, about the only pure commercial products we see any more are the Google Search Appliance and Recommind. And Google recently announced that the appliance is scheduled to go ‘end of life’ over the next few years. All of those bright yellow boxes become really nice Dell servers by the end of 2018.

A new crop of search platforms has grown to fill the void.

As an open source product, Solr has grown in its capabilities, and is now widely used for enterprise search and data applications in corporations and government projects. Solr Cloud extends the platform to a scalable high-availability platform for demanding enterprise and data search applications. Solr is an open source solution.

Cloudera also bundles some interesting extra tools including Solr in their HUE bundle; free to download and free to use as long as you like. Cloudera runs a slightly older but stable release, 4.10; but with a committers Yonik Seeley and Mark Miller, I suspect they’re in a good position.

Hortonworks, a Cloudera competitor, also offers Solr/Solr Cloud in their releases, in partnership with Lucidworks - a company with a large number of committers on staff.

There are also three companies that have proprietary offerings based on open source technology.

Attivio, founded in 2007, is a “Leader” in the most recent Gartner Magic Quadrant for Enterprise Search. Their product, while not open source, nonetheless thrives by combining search, BI, data automation, analytics and more.

Elasticsearch has evolved into a strong platform for search and data analytics, and a number of organizations are finding it useful in some tradition enterprise search applications as well. Elastic has also integrated Kibana, a powerful graphical presentation tool that adds value for content analytics, not just search activity reporting.

Lucidworks Fusion is a relative newcomer to enterprise search. It includes many of the rich architectural features that enterprises expect, including a powerful crawler, connectors, and reporting. With its ‘Anda’ crawler and connectors, admin UI, and reporting, some people see it as a contender to replace the Google Search Appliance.

The one thing that all of these ‘proprietary’ products have in common? They are based on Apache Lucene to deliver critical functionality. And when you consider all of the web sites that use some form of Lucene for their site search, I think you'd agree that it really is a powerful little package. It’s available for virtually any operating systems, and can be integrated using just about any programming language from C/C++ to Java to Perl to Python to .NET.

Even more amazing is that these companies with commercial products based on Lucene – and who compete in the marketplace - actually cooperate when it comes time to fix bugs or add new capabilities to Lucene. Given all of the commercial players that have closed their doors - leaving their customers to find replacement platforms – we’ve reached the point where open-source-based software really is the safe choice now. And universally, Lucene is the common element.

The quirky little search API Doug Cutting put together in 1999 has evolved to be the platform that drives the leading search platforms used in big data, NoSQL, enterprise search, and search analytics. And it doesn’t seem like it’s going to be phasing out any time soon.

May 31, 2016

The Findwise Enterprise Search and Findability Survey 2016 is open for business

Would you find it helpful to benchmark your Enterprise Search operations against hundreds of corporations, organizations and government agencies worldwide? Before you answer, would you find that information useful enough that you’re spend a few minutes answering a survey about your enterprise search practices? It seems like a pretty good deal to me to have real-world data from people just like yourself worldwide.

This survey, the results of which are useful, insightful, and actionable for search managers everywhere, provides the insight into many of the critical areas of search.

Findwise, the Swedish company with offices there and in Denmark, Norway Poland, Norway and London, is gathering data now for the 2016 version of their annual Enterprise Search and Findability Survey at http://bit.ly/1sY9qiE.

What sorts of things will you learn?

Past surveys give insight into the difference between companies will happy search users versus those whose employees prefer to avoid using internal search. One particularly interesting finding last year was that there are three levels of ‘search maturity’, identifiable by how search is implemented across content.

The least mature search organizations, roughly 25% of respondents, have search for specific repositories (siloes), but they generally treat search as ‘fire and forget’, and once installed, there is no ongoing oversight.

More mature search organizations that represent about 60% of respondents, have one search for all silos; but maintaining and improving search technology has very little staff attention.

The remaining 15% of organizations answering the survey invest in search technology and staff, and continuously attempt to improve search and findability. These organizations often have multiple search instances tailored for specific users and repositories.

One of my favorite findings a few years back was that a majority of enterprises have “one or less” full time staff responsible for search; and yet a similar majority of employees reported that search just didn’t work. The good news? Subsequent surveys have shown that staffing search with as few as 2 FTEs improves overall search satisfactions; and 3 FTEs seem to strongly improve overall satisfaction. And even more good news: Over the years, the trend in enterprise search shows that more and more organizations are taking search and findability seriously.

You can participate in the 2016 Findwise Enterprise Search and Findability Survey in just 10 or 15 minutes and you’ll be among the first to know what this year brings. Again, you’ll find the 2016 survey at http://bit.ly/1sY9qiE.

January 20, 2015

Your enterprise search is like your teenager

During a seminar a while back, I made this spontaneous claim. Recently, I made the comment again, and decided to back up my claim - which I’ll do here.

No, really – it’s true. Consider:

You can give your search platform detailed instructions, but it may or may not do things the way you meant:

Modern search platforms provide a console where you, as the one responsible for search, can enter all of the information needed to index content and serve up results. You tell it what repositories to index; what security applies to the various repositories; and how you want the results to look.  But did it? Does it give you a full report of what it did, what it was unable to do, and why?

You really have no idea what it’s doing – especially on weekends:

 Search platforms are notorious for the lack of operational information they provide.

Does your platform give you a useful report of what content was indexed successfully, and which were not – and why? And some platforms stop indexing files when they reach a certain size: do you know what content was not completely indexed?

When it does tell you, sometimes the information is incomplete: 

Your crawler tells you there were a bunch of ‘404’ errors because of a bad or missing URL; but will it tell you which page(s) had the bad link? Chances are it does not. 

They can be moody, and malfunction without any notice:

You schedule a full update of you index every weekend, and it has always worked flawlessly – as far as you know. Then, usually on a 3-day weekend, it fails. Why? See above.

When you talk to others who have search, theirs always sounds much better than yours:

As a conscientious search manager, you read about search, you attend webinars and conferences, and you always want to learn more. But you wonder why other search mangers seem to describe their platform in glowing terms, and never seem to have any of the behavioral issues you live with every day. It kind of makes you wonder what you’re doing wrong with yours.

It costs more to maintain than you thought and it always needs updates:

When you first got the platform you knew there we ongoing expenses you’d have to budget – support, training, updates, consulting. But just like your kid who needs books, a computer, soccer coaching, and tuition, it’s always more than you budgeted. Sometimes way more!

You can buy insurance, but it never seems to cover what you really need:

Bear with me here: you get insurance for your kids in case they get sick or cause an accident, and you buy support and maintenance for your search platform.  But in the same way that you end up surprised that orthodontics are not fully covered, you may find out that help tuning the search platform, or making it work better, isn’t covered by the plan you purchased – in fact, it wasn’t even offered. QED.

It speaks a different vocabulary:

You want to talk with your kid and understand what’s going on; you certainly don’t want to look uncool. But like your kid, your search platform has a vocabulary that only barely makes sense to you. You know rows and columns, and thought you understood ‘fields’; but the search platform uses words you know but that don’t seem to be the same definition you’ve known from databases or CMS systems.

It's hard for one person to manage, especially when it's new:

Many surveys show that most companies have one (or less) full-time staff responsible for running the search engine – while the same companies claim search is ‘critical’ to their mission.  Search is hard to run, especially in the first few years when everything needs attention. You can always get outside help – not unlike day care and babysitters – but it just seems so much better if you could have a team to help manage and maintain search to make it behave better.

How it behaves reflects on you:

You’re the search manager and you’ve got the job to make search work “just like Google”.  You spent more than $250K to get this search engine, and the fact that it just doesn’t work well reflects badly on you and your career. You may be worried about a divorce.

It doesn’t behave like the last one:

People tend to be nostalgic, as are many search managers I know. They learned how to take care of the previous one, but this new one – well, it’s NOTHING like the earlier one. You need to learn its habits and behaviors, and often adjust your behavior to insure peace at work.

You know if it messes up badly late at night, even on a weekend or a holiday, you’ll hear about it:

If customers or employees around the world use your search platform, there is no ‘down time’: when it’s having an issue, you’ll hear about it, and will be expected to solve the issue – NOW. You may even have IT staff monitoring the platform; but when it breaks in some odd and unanticipated way, you get the call. (And when does search ever fail in an expected way?)

 You may be legally responsible if it messes up:

Depending on what your search application is used for, you may find yourself legally responsible for a problem. Fortunately, the chances of you personally being at fault are slim, but if your company takes a hit for a problem that you hadn’t anticipated, you may have some ‘career risk’ of your own. Was secure content about the upcoming merger accidentally made public? Was content to be served only to your Swiss employees when they search from Switzerland exposed outside of the country? And you can’t even buy liability insurance for that kind of error.

When it’s good, you rarely hear about it; when it's bad, you’ll hear about it:

Seriously, how many of you have gotten a call from your CIO to tell you what a great experience he or she had on the new search platform? Do people want to take you to lunch because search works so well? If you answered ‘yes’ to either of these, I’d like to hear from you!

In my experience, people only go out of their way to give feedback on search when it’s not working well. It’s not “like Google”. Even though Google has hundreds or people and ‘bots’ examining every search query to try to make the result better, and you have only yourself and an IT guy.

You’ll hear. 

The work of managing it is never done:

The wonderful southern writer Ferrol Sams wrote :

“He's a good boy… I just can't think of enough things to tell him not to do.” Sound like your search platform? It will misbehave (or fail outright) in ways you never considered, and your search vendor will tell you “We’ve never seen a problem like that before”. Who has to get it fixed? You have to ask?

Once it moves away, you sometimes feel nostalgic:

Either you toss it out, or a major upgrade from your vendor comes alone and the old search platform gets replaced. Soon, you’re wishing for the “Good old days” when you knew how cute and quirky the old one was, and you find yourself feeling nostalgic for it and wishing that it didn’t have to move out.

Do you agree with my premise? What  have I missed?

September 18, 2014

Lucidworks ships Fusion 1.0 - Pretty exciting next gen platform.

OK, I've known about this coming for a while, just didn't know when until this afternoon - so I stayed up late to get the download started after midnight.

Fusion is more than an updated release of Lucidworks Search. It is Solr based, but it's a re-write from top to bottom. And it's not a bare bones search API only a developer can love. Connectors? Check. Security? Check. Analytics? Check. Entity extraction? Check. All included. 

But what it adds is where the real capabilities and contributions are. Machine learning? Check. Admin console? Check. Machine learning? Check. Log analytics? Check. A document pre-processing pipeline? Check. Deep signal processing (think 'automated context processing')? Check. 

Even if you think these new unique capabilities are not your style, then you can buy Solr support and still get licenses for connectors, entity extraction, and a handful of other formerly 'premium' products. Want it all? License the full product at a per-node price I always thought was underpriced. I'm sure you'll be hearing alot more in the coming days and weeks, but go - download - try - and see what it does for your sites. Your developers will love it, your business owners will love it, your users will love it, and I bet even your CFO will love it.  

Full disclosure: I am a former employee of Lucidworks; but I'd be just as excited even if I were not. Go download it for sure and try it on your content. But be sure to check out the  'search as killer app' video on Lucid's home page www.lucidworks.com

s/ Miles

 

 

September 09, 2014

Sometimes you're just wrong! (Maybe).

OK, this one falls into the 'eat your own words' category, so I have to come clean. Well, partly clean. Let me explain.

I was out of town last week, but just before I left I wrote an article asserting that Elasticsearch really isn't 'enterprise' search. The article drew alot of attention and comments from both sides of the argument. I have to say I still think that's the case, but an announcement by Microsoft seems to differ, and end up a net positive for Elasticsearch. Microsoft tells us that Elasticsearch is the platform under the covers of Microsoft's Azure search offering. It looks like you have a couple of options - as long as you're on Azure:

a) You can download and use the open source Elasticsearch platform available on GitHub; or

b) Use Microsoft's managed service 'Facetflow Elasticsearch' which incorporates (some of) the open source code in various places.

Microsoft calls this "a fully-managed real-time search and analytics service" while, according to ZDNet, it is for 'web and mobile application developers looking to incorporate full-text search into their applications'. 

Either way, it's certainly yet another step forward for Elasticsearch, and is a big step forward in visibility for the company. It's not clear what kind of revenue they will receive from the deal - Microsoft being relatively famous for being quite frugal. And after all, smart search folks like Kevin Green of Spantree Technology Group talk about its strengths and liabilities, saying it *is* fast ('wicked fast'); fault-tolerant; distributed and more. But it is not a crawler; a machine learner; a user-facing front end, and it is not secure. 

So I'll agree a partial 'mea culpa' is in order; adding capabilities to an open source project can make it more enterprise ready. But I think the jury may still be out on the rest of my piece. Stay tuned!

August 25, 2014

Is Elasticsearch really enterprise search?

Not too long ago, Gartner released it's the 2014 Magic Quadrant which I’ve written about here and which has generated a lively discussion on the Enterprise Search Engine Professionals group over on LinkedIn.

Much of the discussions I’ve seen about this year's MQ deals with the omission of several platforms that most people think of as 'enterprise search’. Consider that MQ alumni Endeca, Exalead, Vivisimo, Microsoft FAST, and others don’t even appear this year. Over the last few years larger companies acquired most of these players, but in the MQ it's as if they simply ceased to exist.

The name I've heard mentioned besides these previous MQ alumni is Elasticsearch, a relatively new start-up. Elasticsearch, based on Apache Lucene, recently had a huge round of investment by some A-List VCs. What's the deal, Gartner?

Before I share my opinion, I have to reiterate that, until recently, I was an employee of Lucidworks, which many people see as a competitor to Elasticsearch. I believe my opinions are valid here, and I believe I’m known for being vendor-neutral. I think the best search platform for a given environment is a function of the platform and the environment – what data source, security, management and budget apply for any given company or department. “Search engine mismatch’ is a real problem and we’ve written about it for years.

Given that caveat, I believe I’m accurately describing the situation, and I encourage you to leave a comment if you think I've lost my objectivity!

OK, here goes. I don't believe Elasticsearch is in the enterprise search space. For that reason, if for no other, it doesn’t belong on the Gartner Magic Quadrant for search.

You heard it here. It's not that I don't think Elasticsearch isn’t a powerful, cool, and valuable tool. It is all that, and more. As I mentioned, it’s based on Apache Lucene, a fantastic embedded search tool. In fact, it's the same tool Solr (and therefore Lucidworks' commercial products) are based on.  But Lucene by itself is a tool more than a solution for enterprise search.

Let me start by addressing what I think Elasticsearch is great for: search-enabled data visualization. The first time I attended an Elasticsearch meet-up, they were showing the product in conjunction with two other open source projects: Logstash and Kibana. The total effect was great and made for a fantastic demo! I was fully and completely impressed, and saw the value immediately - search driving a visualization tool that was engaging, interactive, and exciting! 

Since then, Elasticsearch has apparently hired the guys who created those two respective open source projects, and has now morphed into a log analytics company - more like Splunk with great presentation capability, and less like traditional enterprise search. Their product is ELK - Elasticsearch Logstash Kibana. You can download all of these from GitHub, by the way.

(Lucidworks has also seen the value of Kibana to enterprise search, and has released their own version of Logstash and Kibana integrated with Solr called SiLK (Solr-Integrated Logstash and Kibana).

Now let me tell you why I do not think of Elasticsearch as an enterprise search solution. First, in my time at Lucid, I'm not aware of any enterprise opportunities that Lucidworks lost to ELK. I could be wrong, and maybe the Elastic guys know of many deals we never saw at Lucid. But with no crawler and other components I consider ‘required’ as part of an enterprise search product, I'm not sure they're interested - yet, at least.

Next, check the title of their home page: "Open Source Distributed Real Time Search". Doesn't scream 'Google Search Appliance replacement', does it? Read Elasticsearch founder Shay Banon on the GSA.

Finally, Wired Magazine has an even more interesting quote: Shay Banon on SharePoint. “We're not doing enterprise search in the traditional sense. We're not going to index SharePoint documents”.

Now, with the growth and the money Elasticsearch has, they may change their tune. But with over $100M in venture capital now, I think their investors are valuing Elasticsearch as a Splunk competitor, and perhaps a NoSQL search product for Hadoop - not a traditional enterprise search engine. 

So the real question is: which space are you in? Enterprise Search with SharePoint and other legacy data sources? Web content and file shares you need a crawler for? Is LDAP or Active Directory security important to you? Well - I won't say 'no way' - but I'd want to see it before I buy.

Do you use Elasticsearch for your enterprise search? Let me hear from you!

 

 

 

August 21, 2014

More on the Gartner MQ: Fact or fiction?

There is a lively discussion going on over in the LinkedIn ‘Enterprise Search Engine Professionals’ group about the recent Gartner Magic Quadrant report on Enterprise Search. Whit Andrews, a Gartner Research VP, has replied that the Gartner MQ is not a 'pay to play'. I confess guilt to have been the one who brought the topic up in these threads, at least, and I certainly thank Whit for clarifying the misunderstanding directly.

That said, two of my colleagues who are true search experts have raised some questions I thought should be addressed.

Charlie Hull of UK-based Flax says he's “unconvinced of the value of the MQ to anyone wanting a comprehensive … view of the options available in the search market'. And Otis Gospodnetić of New York-based Sematext asks "why (would) anyone bother with Gartner's reports. We all know they don't necessarily match the reality". I want to try to address those two very good points.

First, I'm not sure Gartner claims to be a comprehensive overview of the search market. Perhaps there are more thorough lists- my friends and colleagues Avi Rappoport and Steve Arnold both have more complete coverage. Avi, now at Search Technologies, still maintains   

www.searchtools.com with a list that is as much a history of search as a list of vendors. And Steve Arnold has a great deal of free content on his site as well as high quality technology overviews by subscription. Find links to both at arnoldit.com.

Nonetheless, Gartner does have published criterion, and being a paid subscriber is not one of them. His fellow Gartner analyst French Caldwell calls that out on his blog. By the way, I have first-hand experience that Gartner is willing to cut some slack to companies that don't quite meet all of their guidelines for inclusion, and I think that adds credence to the claim that everything.

A more interesting question is one that Otis raises: “why would anyone bother with Gartner's reports”?

To answer that, let me paraphrase a well-known quote from the early days of computers: "No one ever got fired for following Gartner's advice". They are well known for having good if not perfect advice - and I'd suspect that in the fine print, Gartner even acknowledges the fallibility of their recommendations. And all of us know that in real life, you can't select software as complex as an enterprise search platform without a proof of concept in your environment and on your content.

The industry is full of examples where the *best* technology loses pretty consistently to 'pretty good' stuff backed by a major firm/analyst/expert. Otis, I know you're an expert, and I'd take what you say as gospel. A VP at a big corporation who is not familiar with search (or his company's detailed search requirements) may not do so. And any one on that VP's staff who picks a platform based solely on what someone like you or I say probably faces some amount of career risk. That said, I think I speak for Otis and Charlie and others when I say I am glad that a number of folks have listened to our advice and are still fully employed!]

So - in summary, I think we're all right. Whit Andrews and Gartner provide advice that large organizations trust because of the overall methodology of their evaluation. Everyone does know it's not infallible, so a smart company will use the 'trust but verify' approach. And they continue to trust you and I, but more so when Gartner or Forrester or one of the large national consulting companies conforms our recommendation. And of not, we have to provide a compelling reason why something else is better for them. And the longer we're successful with out clients, the more credible we become.