Mongo vs Elastic

I’ve been lurking and enjoyed reading about Saul’s latest portfolio review. I have many of the same stocks and have had a fantastic quarter also.

I’ve read a bunch about Elastic and Mongo, and I thought I’d just present my view on these two companies.

For one thing, both have great technologies. But from a business model point of view, I consider these companies almost opposites, for companies playing in almost the same space.

Mongo has a general NoSql database that can be used for the vast majority of data use cases. It’s a swiss army knife - no matter what you want to do, they have a blade for it. Every single thing on any computer has one or more databases attached to it. Mongo is a contender for the vast majority of these.

And Mongo has a plan to dominate. They have their Atlas hosted product, which makes it much easier to use over hosting your own (even for free). Their code is completely open source, which makes people comfortable to use it - no matter what happens, it is out there and someone will be available to support it.

And they have thought through the business model and are focused on winning - they didn’t respond to someone eating their lunch. They anticipated it and created something brand new that hasn’t been done before in an open source company - their SSPL license. They are not only innovating in their technology, they are innovating in their business model. We’ll let the open source evangelists debate over this is a proper open source license, but it is the opposite of proprietary - it only says that if you want to use Mongo to create a cloud offering, you have to make your cloud offering open source too. Even if it is sneaky, it sure is open :slight_smile:

Mongo’s R&D is also going gangbusters, with ACID (multi-document) transactions, WiredTiger engine for multiple data views, and the Stitch serverless offering. And the great thing is they have positioned themselves to be able to stay on top even if better technologies come up in specific areas of the market - they will just copy/buy their way to stay on top. This is a company that is set up to dominate for 20 years.

Elastic has a very good full text search product. It is excellent technology, and full text search is a common and growing need in our new world of search buttons everywhere. Lots of people are looking for a good product in this area, so it makes sense that they will have explosive early growth.

But don’t think they have the same type of potential trajectory as Mongo. The size of their market with such a focused product is smaller. They are also very susceptible to someone building a better mousetrap. The next company that builds a better full text search is going to take away Elastic market share - what are they going to do to stop it, when this is all they do?

I also don’t think they have thought through their business model very well. Open source companies always need to find a way to monetize their products, so they can make back their investment and profit. Elastic chose to open source part of their system, and keep closed some of their key value adds.

This is not a model that has worked very well - small players and individual developers who don’t have the money to pay, still need a fully functioning system. It also creates confusion about what is open and what isn’t.

I don’t consider the Amazon Open Distro to be pure FUD, the way their DocumentDB is. Open Distro addresses that very weakpoint in their model - that some of their key value add is proprietary. This frustrates lots of developers and small shops. I think Amazon has a decent chance of making a go of Open Distro - if that works, it will be extremely painful for Elastic.

So over all, I’m not an investor in Elastic, though I may be an occasional trader if their valuation goes very low or high. I do expect them to do great over the short run, but I think Elastic has far too many risks over the long run.



Mongo has a general NoSql database that can be used for the vast majority of data use cases.

SteppenWulf, I know you know this, but for the sake of less knowledgeable readers I would like to amend this a little. There are a number of different NoSQL database types (probably better called Not Relational). They are known as NoSQL as a group mostly because they are not relational and relational has so hugely dominated the database market for years, but they are of several different types and those types are quite different and appeal to different use cases. Mongo is one of the fairly popular Document types which address a very broad use case of unstructured or poorly structured documents, which don’t fit well into the relational model. But, that doesn’t mean that it is a good solution for use cases that fit well into the relational model, as do most transaction processing applications.


I think to look at Elastic as only word search is to greatly limit their stack. That is but one use case of which there are an ever growing assortment.

When I see something like this, it looks like there is an enormous opportunity in many directions.…

For six years, ORNL’s cybersecurity team used Splunk as their SIEM.

With Elasticsearch, ORNL was able to deploy a SIEM that increased speed and security. Today, the lab’s production architecture runs 25 Elasticsearch nodes, all within Docker, across 25 virtual machines. Their system ingests over two billion documents each day

There is a lot more to Elastic search than enterprise/app search.



Smorgasboard, I understand their strong position in full text search, as you said is a small market. Which means they will hit a brick wall on growth sooner. However they are entering new markets. I am concerned they are trying to retrofit their search technology for data analysis to make a 2nd rate product. At the same time they are entering big markets. Big data and log analytics, and finding new uses for their technologies.

I don’t know how successful they will be there, or how successful they are now.

Your opinion on ESTC outside of search?

I am watching this one with interest but concerned of decelerating growth.

I thought the only thing to watch out for at this time is the shares lockup. I think that is why everyone is holding off.

Again I wonder what other stock that was in this situation fared.

Mongo is one of the fairly popular Document types which address a very broad use case of unstructured or poorly structured documents, which don’t fit well into the relational model. But, that doesn’t mean that it is a good solution for use cases that fit well into the relational model, as do most transaction processing applications.

My view on the future of NoSql and Mongo is not the majority view, so take it with a grain of salt. But I think that over time, NoSql will take over most data stores, and that the relational model is irrelevant. I don’t think the rise of NoSql has anything to do with storing unstructured data. We’ve always been able to do that in blobs and on the file system.

There is a theorem called CAP which says that in a partitioned system (meaning you have need more than one data server) you can have either availability or consistency, but not both. So if one of your servers goes down, you can keep going. You will be eventually consistent - the server will come back up, and you can clean up any mess. But while that one server is down, you are available but not fully consistent.

Alternatively you can wait until all the servers are up, which means that you won’t be available if any of your servers go down. This also applies to data handling speed, so systems that focus on availability are much faster than those that focus on consistency.

SQL tries to guarantee consistency, with things like ACID transactions. NoSql focuses on availability, which means it can handle much larger data sets, much more quickly, while being always available. It guarantees eventual consistency, but not consistency at every point in time.

If we take a look at business use cases, I think we will see that 99% of use cases care more about availability than immediate consistency - as long as you can guarantee eventual consistency - and this is what NoSql does. Mongo has even provided the ability to handle your 1% that need immediate consistency with their ACID multi-document transactions.

So my view is there are no relational data sets - only available vs consistent ones, and the vast vast majority of those will suit a NoSql data store.

Besides, every NoSql data store models relations between its data elements, and Sql is just one style of relationship representation. 20 years from now we won’t even remember what we meant when we talked about relational data sets



I was expecting an argument that Elastic is about more than search - thanks. I know they are trying to expand in different directions. The ELK stack (Elastic + Logstash + Kibana) is a real competitor to Splunk, but it is combining three separate open source projects (so really hard to monetize), and is also a real pain to run and maintain, according to my dev-ops friends.

In general, sure they have potential, but I think it is unproven if they can be dominate in any area except search.

I’m not going to put my money into unproven potential, especially at these prices. They are dominant in full text search - here is there real value. But I don’t see a winning business model yet, I think they are struggling to monetize their tech, and they have so much competition and so much of it is free.

It just all looks too risky to me, at this point. But I’ll be happy to trade them - I think they are going to have some great quarters - just not sure how long the party will last.



I think you were addressing me, right? I think we pretty much agree - Elastic doesn’t have the potential growth and there is a real risk of slowing growth once they get the low hanging fruit. There other potential growth areas are unproven

1 Like

Hey SteppenWulf, I too have been lurking :slight_smile:

I’m very familiar with ElasticSearch, and NoSQL, less so with Mongo specifically.

My premise is that ElasticSearch actually has a larger TAM than MongoDB, because theres less competition in the search/aggregation space.

If you want a database, theres a wide variety of choices, relational, nosql, graph etc., and some percent will go with Mongo, and many others will stick with whatever their thing is. Relational databases still work (extremely) well for almost every use-case.

If you want distributed search [note: “full text search product” is not what ElasticSearch is - “distributed search (of all flavours not just text), aggregation, and visuals” might be a bit closer] your options are much more limited.

So you can stuff ElasticSearch on top of a relational database, or on top of MongoDB, or on the side, processing logs and machine performance etc.

In my experience, ElasticSearch quickly becomes a ‘dump-it’ datastore. Where are we going to put our log files? Dump-it in ElasticSearch. Where are we going to put our raw data? Dump-it in ElasticSearch.

The use-case then tends to widen into search, aggregation and visuals, something ElasticSearch excels at.

So I think that ElasticSearch is a bigger bet than Mongo. I could be (probably am?) wrong :slight_smile:

I also don’t think that ‘building a better ElasticSearch’ is any different to ‘building a better NoSql database’, the complexity for both is similar (ie, very complex).

OpenDistro is a potential concern, I haven’t seen Amazon go that aggressively against other open-source projects, but I’ll wait and see. ElasticSearch (base version) is also extremely capable without the x-pack stuff.

I have concerns about the business-model and valuation as well, so I’ve lightened both as their multiples have expanded, and look to buy back as their multiples contract. Thats not what Saul does (I don’t think) but its more in line my my investing approach.



unproven potential

You miss the whole part from the article about ORNL, you know the world’s largest data research center and home to the world’s faster computer using Elastic at massive scale to leverage ELK for SEIM. And displaced a legacy titan in the space.

That’s just an example. Albeit an extremely huge one at that.



Greg, I absolutely agree with you. It seems the concern is distrust of management. Is management really creating a business model that works?

To date Elastic is growing faster, including faster customer growth numbers, and has more revenue per customer. Thus they are doing something objectively “superior” to even Mongo although their aggregate revenues and customer count are about a quarter or two quarters of reporting behind where Mongo is. Mongo did accelerate this quarter somthey May pull ahead. But to date Elastic has grown revenues faster, customers faster, and makes more revenue per customer than Mongo.

Competition wise very astute. Elastic can fit any database, not just a choice amongst many. The question becomes, for both Elastic and Mongo, how many can they monetize?

I think this question is misunderstood. Out of what, 60 million downloads, give or take Mongo has 9000 some customers. Out of 300 million give or take downloads Elastic has 7200 customers, up 900 just last Q. That is a very small percentage of downloaders that actually result into customers. And yet this cream of the crop is a very large market of eventually 10s if not 100,000 customers or more.

I think we lose focus when those who use for free interfere w actually understanding the business model. Both Mongo and Elastic make money only on the very top 1% tier and everyone else plays for free. Just because they do does not mean the business model is broken. That is their business model.

Mongo is becoming more proprietary like now. More traditional software model. So it may play out differently. W Elsstic they intend to continue to use the benefits of open source to greatly enhance the reach of their marketing and R&D so that they remain un new mouse trappable and the growing and dominant world leader in an ever growing market somthat more and more mission critical use cases are born and run. Such use cases worthwhile of paying lots of money for those features Elastic owns.

To date it’s worked for both companies brilliantly. Mongo is making a more proprietary like change that may make its open source claim less than it was, and Elastic has to adapt to Amazon trying to neuter their use of open source.

This comes down to management and whether you trust they know what they are doing or not. Clearly easier to understand and trust the more standard software model that Mongo is running, and less easy to understand and trust the more novel open source business model Elastic is running.

Either way, Elastic is not just web site search. They are far more than that and drove Google out of the market, their nearest peer is not open source and far smaller, and Splunk is already seeing some disruption and not so much the other way. So trust in management and numbers and current real world results or just admitting the business model won’t work.

I don’t know which answer is correct. I tend strongly to agree w the side that follow the numbers, the real world results, and that management knows what they are doing. I can understand not taking this position however. Perhaps more power to investors if this creates a wall of worry to climb. Beats the wall of despair and destruction - yikes!




Btw I want to add that Elastic controls and owns their code as much as Mongo. This creates advantages.

As an example thenfree product Canvas that is a new Tableau like product that enables you to visualize data in the Elastic database is only licensed by Elastic. Not by Amazon. Not by Open Distro. You want to use it, you use Elastic. The same with all the proprietary features whether Elastic charges for them or not.

The Mongo 3.6 code is available for anyone, including Amazon to use as their core code to build Out proprietary extensions, just like the Elastic core code is. Some say Elastic’s core code is more valuable than Mongo’s 3.6 code is. I’m not so sure about this. Almost all Mongo use cases can be satisfied with 3.6. However, the tiny smidgen that pay want all the bells and whistles. Thus 4.0 creates the money.

There is nothing stopping anyone from building those bells and whistles directly off 3.6 now other than it is not easy.

Similarly, nothing stopping someone f doing the same to try to replicate x-pack, Canvas and the like. Just not easy to do or Amazon would have done so already.

Any event, functions like Canvas are only available w in the Elastic license. Suppose to be one reason to continue long term loyalty to Rlastic and not an emulator attempting to imitate the proprietary aspects.



In my experience, ElasticSearch quickly becomes a ‘dump-it’ datastore. Where are we going to put our log files? Dump-it in ElasticSearch. Where are we going to put our raw data? Dump-it in ElasticSearch.

The use-case then tends to widen into search, aggregation and visuals, something ElasticSearch excels at.

36 times the word “use cases” can be found in the most recent ER CC transcript.

Elastic (ESTC) CEO Shay Banon on Q3 2019 Results - Earnings Call Transcript $ESTC

“We’ve seen these at Samsung SDS who closed new business with us in the quarter. I had the pleasure of meeting with them last week at our Elastic{ON} Tour event in Soho[ph]. They used Elastic for security analytics and many other use cases, such as enterprise search, app search, logging, infrastructure monitoring for many Samsung businesses within the Samsung Group.”

“One example is Rico Group, a Japanese multinational imaging and electronics company who recently renewed and expanded their business with us. I met with the team there, and I was blown away watching them demo what they’ve built. They replaced their initial logging solution with Elastic, which has become an integral part of their security analytics, customer service and network operation infrastructure. I love it when several use cases are woven together and have a compounding effect on an organization.”

“As of 6.6 release this quarter, we’ve applied DKD 3 to GeoShape analysis. So we’ve moved from analyzing dots to areas, which can be more involved because we are talking about the analysis of more complex shapes, like bike trails, voting districts, state borders, and bus and shipping lines.”

"I’m also proud to say that all of our APM agents are compatible with OpenTracing, which is a vendor neutral way to introduce Distributed tracing into applications. OpenTracing is a project of the Cloud Native Computing Foundation. I shared this because we formally became members of this foundation in the quarter.

This is meaningful to us for a few reasons: It strengthens our commitment to open standards. It demonstrates our capabilities with technologies like Kubernetes and Prometheus. We even previewed Helm Charge in Elastic in the quarter. Lastly, it shows our investments in Cloud Native Technology stacks and the observability space. Continuing to invest here remains important to us, so much so that we’ve organized some of our engineering teams around it."

“When I look at that space, the way that I think about it is it feels very similar to how we got adopted in the logging space about three or fourth years ago. What people sometimes forget is that we actually started and people compared us or users competitors to enterprise search solutions and we actually went through an evolution of us being used in the context of logging and I see that playing out now in the security space.”

Read that last sentence over and over again.



You know…simple google searches are your friend, rather than believing definitive and absolute statements that are thrown out and stubbornly adhered to, like Elastic is just text search.

Here is a 2 year old article…which is about 10 years in tech time.

I got a kick out of the first sentence:…

"Other than ‘You Know, for Search’, the uses of Elasticsearch continue to grow and change over time. "

Or here is another guy on the web w a differing opinion. Looks like he updated his answer on what elastic does in mar 2018, which was an uodate to his original 2015 note:…

I felt like the second part is no longer edgy, it’s actually what Elastic as a company has been doing really well in past year. With current DevOps movement, CI/CD pipelines, increasing amount of metrics from various sources, ELK became a defacto choice for infrastructure monitoring, it’s no longer just a distributed RESTful text-search engine. It has an amazing set of products:

Logstash (tons of data inputs)
X-Pack (premium)
Machine Learning
Cross data center metrics
An ecosystem, built by community, is growing around ELK stack that expands current features, few of them worth mentioning:

Search Guard"

Here are a couple more web nerds explaining Elastic:………

Most importantly…who cares. Just follow the numbers each ER.



so take it with a grain of salt

I think I will just disagree with some of it instead! :slight_smile:

Just as document stores can do things that are impossible or difficult to do in a relational database, the reverse is also true. Just as documents are far more powerful than BLOBs with word indexes or even JSON datatypes, relational DBs have many features which are important to transactional applications and are not inherent parts of document stores. Constraints about what values may appear in a particular field are natural in RDBs, while document stores excel in accepting any value without prior knowledge. Constraints about how records are related are natural to RDBs while document stores excel at taking in anything and figuring it out later.

1 Like

Hi SteppenWulf,

You may want to read through the link which has responses from Elastic IR.…

Like some others here I feel good about Elastic’s strong future prospects. I had misgivings about their business model though, less so now after response from IR. For the moment I am going to trust management and follow the numbers.