MongoDB Inc. (NASDAQ:MDB) went down by -7.22% from its latest closing price compared to the recent 1-year high of $590.00. The company’s stock price has collected -20.42% of loss in the last five trading sessions. The Wall Street Journal reported on 12/07/21 that Tesla, Intel, Bitcoin: What to Watch in the Stock Market Today
Is It Worth Investing in MongoDB Inc. (NASDAQ :MDB) Right Now?
Plus, the 36-month beta value for MDB is at 0.79. Opinions of the stock are interesting as 13 analysts out of 19 who provided ratings for MongoDB Inc. declared the stock was a “buy,” while 1 rated the stock as “overweight,” 4 rated it as “hold,” and 0 as “sell.”
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The average price from analysts is $565.79, which is $202.52 above the current price. MDB currently public float of 62.97M and currently shorts hold a 6.70% ratio of that float. Today, the average trading volume of MDB was 1.12M shares.
MDB’s Market Performance
MDB stocks went down by -20.42% for the week, with a monthly drop of -8.19% and a quarterly performance of -31.22%, while its annual performance rate touched -10.88%. The volatility ratio for the week stands at 6.39% while the volatility levels for the past 30 days are set at 6.78% for MongoDB Inc.. The simple moving average for the period of the last 20 days is -12.20% for MDB stocks with a simple moving average of -16.16% for the last 200 days.
Analysts’ Opinion of MDB
Many brokerage firms have already submitted their reports for MDB stocks, with Tigress Financial repeating the rating for MDB by listing it as a “Buy.” The predicted price for MDB in the upcoming period, according to Tigress Financial is $630 based on the research report published on February 11th of the current year 2022.
Credit Suisse, on the other hand, stated in their research note that they expect to see MDB reach a price target of $700. The rating they have provided for MDB stocks is “Outperform” according to the report published on November 16th, 2021.
UBS gave a rating of “Neutral” to MDB, setting the target price at $450 in the report published on September 03rd of the previous year.
MDB Trading at -19.91% from the 50-Day Moving Average
After a stumble in the market that brought MDB to its low price for the period of the last 52 weeks, the company was unable to rebound, for now settling with -39.86% of loss for the given period.
Volatility was left at 6.78%, however, over the last 30 days, the volatility rate increased by 6.39%, as shares sank -2.92% for the moving average over the last 20 days. Over the last 50 days, in opposition, the stock is trading -30.12% lower at present.
During the last 5 trading sessions, MDB fell by -20.42%, which changed the moving average for the period of 200-days by +39.47% in comparison to the 20-day moving average, which settled at $403.56. In addition, MongoDB Inc. saw -32.97% in overturn over a single year, with a tendency to cut further losses.
Insider Trading
Reports are indicating that there were more than several insider trading activities at MDB starting from Ittycheria Dev, who sale 33,692 shares at the price of $449.01 back on Feb 10. After this action, Ittycheria Dev now owns 196,390 shares of MongoDB Inc., valued at $15,128,045 using the latest closing price.
Ittycheria Dev, the President & CEO of MongoDB Inc., sale 35,000 shares at $398.11 during a trade that took place back on Feb 04, which means that Ittycheria Dev is holding 196,390 shares at $13,933,724 based on the most recent closing price.
Stock Fundamentals for MDB
Current profitability levels for the company are sitting at:
-35.45 for the present operating margin
+68.57 for the gross margin
The net margin for MongoDB Inc. stands at -45.22. The total capital return value is set at -19.86, while invested capital returns managed to touch -25.52. Equity return is now at value -111.70, with -16.10 for asset returns.
When we switch over and look at the enterprise to sales, we see a ratio of 32.91, with the company’s debt to enterprise value settled at 0.05. The receivables turnover for the company is 5.35 and the total asset turnover is 0.43. The liquidity ratio also appears to be rather interesting for investors as it stands at 3.12.
In last trading session, MongoDB Inc. (NASDAQ:MDB) saw 1.3 million shares changing hands with its beta currently measuring 0.79. Company’s recent per share price level of $354.81 trading at -$27.62 or -7.22% at ring of the bell on the day assigns it a market valuation of $24.86B. That closing price of MDB’s stock is at a discount of -66.29% from its 52-week high price of $590.00 and is indicating a premium of 32.92% from its 52-week low price of $238.01. Taking a look at company’s average trading volume for last 10-days demonstrates a volume of 0.99 million shares which gives us an average trading volume of 1.12 million if we extend that period to 3-months.
For MongoDB Inc. (MDB), analysts’ consensus is at an average recommendation of an Overweight while assigning it a mean rating of 1.90. Splitting up the data highlights that, out of 19 analysts covering the stock, 0 rated the stock as a Sell while 1 recommended an Overweight rating for the stock. 4 suggested the stock as a Hold whereas 13 see the stock as a Buy. 1 analyst(s) advised it as an Underweight. The company is expected to be making an EPS of -$0.22 in the current quarter.
Upright in the red during last session for losing -7.22%, in the last five days MDB remained trading in the red while hitting it’s week-highest on Wednesday, 02/16/22 when the stock touched $354.81 price level, adding 19.79% to its value on the day. MongoDB Inc.’s shares saw a change of -32.97% in year-to-date performance and have moved -20.42% in past 5-day. MongoDB Inc. (NASDAQ:MDB) showed a performance of -8.19% in past 30-days. Number of shares sold short was 4.49 million shares which calculate 4.11 days to cover the short interests.
Wall Street analysts have assigned a consensus price target of $565.79 to the stock, which implies a rise of 37.29% to its current value. Analysts have been projecting $400.00 as a low price target for the stock while placing it at a high target of $700.00. It follows that stock’s current price would drop -97.29% in reaching the projected high whereas dropping to the targeted low would mean a loss of -12.74% for stock’s current value.
MongoDB Inc. (MDB) estimates and forecasts
Statistics highlight that MongoDB Inc. is scoring comparatively higher than the scores of other players of the relevant industry. The company lost -7.64% of value to its shares in past 6 months, showing an annual growth rate of 26.26% while that of industry is -1.50. Apart from that, the company came raising its revenue forecast for fiscal year 2022. The company is estimating its revenue growth to increase by 33.30% in the current quarter and calculating -13.30% decrease in the next quarter. This year revenue growth is estimated to rise 43.80% from the last financial year’s standing.
12 industry analysts have given their estimates about the company’s current quarter revenue by setting an average figure of $241.76 million for the same. And 13 analysts are in estimates of company making revenue of $253.75 million in the next quarter that will end on Apr 2022.
Weighing up company’s earnings over the past 5-year and in the next 5-year periods, we find the company posting an annual earnings growth rate of -24.70% during past 5 years.
MDB Dividends
MongoDB Inc. is more likely to be releasing its next quarterly report between March 07 and March 11 and investors are confident in the company announcing better current-quarter dividends despite the fact that it has been facing issues arising out of mounting debt.
MongoDB Inc. (NASDAQ:MDB)’s Major holders
Insiders are in possession of 7.58% of company’s total shares while institution are holding 90.05 percent of that, with stock having share float percentage of 97.44%. Investors also watch the number of corporate investors in a company very closely, which is 90.05% institutions for MongoDB Inc. that are currently holding shares of the company. Capital World Investors is the top institutional holder at MDB for having 6.8 million shares of worth $3.21 billion. And as of Sep 29, 2021, it was holding 10.19% of the company’s outstanding shares.
The second largest institutional holder is Price (T.Rowe) Associates Inc, which was holding about 6.68 million shares on Sep 29, 2021. The number of shares represents firm’s hold over 10.01% of outstanding shares, having a total worth of $3.15 billion.
On the other hand, Growth Fund Of America Inc and Smallcap World Fund are the top two Mutual Funds which own company’s shares. As of Nov 29, 2021, the former fund manager was holding 4.81 million shares of worth $2.39 billion or 7.20% of the total outstanding shares. The later fund manager was in possession of 1.91 million shares on Sep 29, 2021, making its stake of worth around $898.76 million in the company or a holder of 2.86% of company’s stock.
Posta: I’m going to be talking about the top five challenges of running a service mesh in an enterprise. My name is Christian Posta. I’m a VP and a Field CTO here at solo.io. Here at Solo, we focus on application networking, and connecting, securing, observing various services across clouds, across clusters, regions, zones, and so on. I’ve been here almost three years, been focused on integration and distributed systems, and building cloud architectures for quite some time now. Author of a few books, including a book that will be released in the next few months, called, “Istio in Action” from Manning.
What Solo Offers
At solo, we’re working on application networking, and doing that in a way that better fits cloud architectures and modern architectures. We have two main products, Gloo Edge, which is our modern API gateway, and Gloo Mesh, which is our enterprise service mesh. We’ve seen in the analyst reports recently how our vision, our products, how we compare to our competitors, start to outperform. Service mesh is still relatively new, evolving, and maturing space. You can see in one of the first analyst reports that we perform very strongly. As of last week, we made public that we raised our Series C at a billion dollar valuation. This is definitely a testament to our customers, the work we’re doing with the industry, and working with organizations deploying Envoy based technology at massive scale, including service mesh, Istio, and these types of things, and the tremendous success that we’ve had.
Service Connectivity
This is an area of very deep interest for us at Solo. We are service mesh experts. We are application networking experts, through and through. Let’s take a look at some of the challenges that we’ve seen organizations face as they start to adopt this technology or the next phase of modernizing their application infrastructure. The talk is running a service mesh, and some of the challenges of adopting it. We might want to take a step back and understand, what is the challenge, what is the problem that we’re trying to solve with a mesh? It’s around service connectivity, partially. I think that’s a big tactical part of why we’re talking about service mesh. Then, operationally, how can we bring and apply policies about how services communicate with each other, independent of how they were written, how they’re deployed. The service mesh brings a lot of value to being able to do that. It is two main areas. One is the technical side, one is more of the operational or efficiency and principal way of how we build and manage these types of infrastructures in the cloud.
Service connectivity, things that we typically worry about: service discovery, load balancing, timeouts, retries, circuit breaking, transport security, observability. These are not optional things to solve, we need to solve them somehow. In the past, we’ve seen the cloud generation even before enterprises started getting in, things like Amazon and Netflix, and so on, how they started to do it, was to build things into the applications themselves. Try to govern the teams so that they use these specific libraries, these particular pieces of infrastructure to implement the patterns correctly but across languages, across different frameworks. Especially, in an organization that has been around for 50 years and is very successful, and now they’re trying to modernize, those types of things get very difficult to operate.
Centralized Approach
Another approach that we saw in large organizations is to stand up some centralized team and system through which all the traffic in the company should flow through, whether that’s enterprise service bus, whether that’s some centralized API Management Server. We’ve seen this approach, but this doesn’t scale very well. The decentralized approach, this scaled fine, it came with other challenges. This does not scale well and has bottleneck challenges, whether that’s the technology, obviously, or more importantly, the processes that built up around these teams and the team that supports service A, how do they go about making changes? They go to some centralized team and say, can you do this for me? Let’s open tickets, and let’s slow things down.
Decentralized Communication between Services
What we want is some balance in between, and that’s where the service mesh and the surrounding and supporting components come into play. It’s the decentralization as well as the self-service and the automation around the policies that would be enforced in the mesh that allow an organization to move faster. That’s the whole point of these modern architectures, and adopting things like containers, Kubernetes, CI/CD, is to move faster. The last missing piece of that is how services communicate with each other. Decentralizing that communication is very important. The service mesh brings a pattern that is based on offloading some of the application networking concerns to something else, an agent, a proxy. In this case, a lot of the service meshes have implemented the proxy with a technology called Envoy. In this model, the application talks, when it talks to the network, talks through this proxy first. When a service communicates with another service, there’s inbound traffic, it goes through this proxy first, and then to the app. These proxies are co-located with the app instance, these are not reverse proxies. They’re actually one to one with the application instance, and become atomically associated with the application.
In these proxies is work we can implement consistently, regardless of what language and framework was used to write the app. We can consistently apply application networking implementations and policies around things like timeouts and retries, and service discovery, and circuit breaking, and load balancing, and not have to worry about what the applications were written in, what frameworks. We can control and manage this stuff remotely. That’s where the control plane starts to come into the picture. Control plane configures the individual proxies that live with each of these instances.
Do You Need a Service Mesh?
This sounds good on one hand. The architecture fits what we’re trying to do by modernizing. The benefits of doing this, decoupling some of these policies, automating them away, removing the burden from developers, actually has a very big win. A lot of value brings a lot of value. Do you need a service mesh? We work with organizations all the time that are going through this process, do they need a service mesh, because maybe they don’t? That’s going to be very context specific, you will have to decide that. Are you building a microservices style architecture? Do you have tens or hundreds of different applications or services that you are deploying? Are you allowing teams to “use the right tool for the job,” or the right language for that particular team’s skill set? Microservices in general are complicated. The more moving pieces you have, the more that you put out over the network, the less you have governed and centralized, it could create a big mess. This is where service mesh, at least on the application networking side can help establish some consistency and some knowns about the system, especially when things start to go wrong.
Are you using things like containers and Kubernetes, or cloud infrastructure that scales elastically? Are you communicating more over the network RPC style, maybe async or messaging based, but typically gRPC, and REST, and GraphQL, and SOAP, and these types of RPC style communications are where a service mesh brings its biggest value. Then, of course, deploying a large set of services, where you need to have some consistency over the policies about how services communicate with each other. If you have an environment that resembles this or will tend toward this, then a service mesh might be a good solution or a good thing to start looking at.
Challenges of Running a Service Mesh at Scale in an Enterprise – Which Service Mesh to Pick
Let’s take a look at some of the challenges of running a service mesh at scale in an enterprise. The first one starts with what service mesh to pick. Over the last three or four years, a lot of different vendors have entered this ecosystem with different options for which service mesh to pick. There are various technologies that are being used, different architectures that are being used, and different strengths or initial focal points of what a particular mesh might be trying to solve. For the most part, a large percentage of the meshes are converging and using Envoy proxy. They’re converging around this technology, which brings a lot of different features for being able to do service to service communication. Some meshes are opting to either reuse technology they already had, or to rebuild something completely new from scratch.
You also want to evaluate, what are your use cases? What is the maturity or battle tested implementations that could support your use cases? We’ve noticed at Solo after observing this market for the last four years, that Istio has become one of the more mature deployments of a service mesh, especially at scale. Especially at an enterprise with a lot of those unique edge cases, that some of the other meshes are still trying to catch up and figure out how to solve, or haven’t even seen those problems yet. Where do you go for help? Service mesh and deploying this technology requires a deep level of expertise. Where can you go for help or partner, either with an open source community or with a vendor of your choice? We see that the community itself has converged around Istio, while some of the others are supported by single vendors. Some don’t have any real commercial support at all.
How Does a Mesh Fit In With Existing API Gateway Technology?
The next question is, how do API gateways fit into this mix? Some meshes have a gateway implementation. Istio is a good example. Have an Istio ingress gateway. Then you start to bring that in, and say, I’ll just use the gateway. Then you realize, I have a need for things like integrating with OIDC, or web application firewalling, or I need to do message transformations. Or I need to do more sophisticated rate limiting or quota policy enforcement. Then you start to build all this stuff yourself. Then the question is, what is the role of API gateway? How does this fit in with service mesh? Am I supposed to go build all this stuff myself? There are solutions. You can just stand up one of your existing API gateways in front of your services and try to route them into a service mesh. You could offload some of the API gateway capabilities to your applications themselves, although that seems to be going in a step backwards. Or you could use an API gateway that is native to Istio or a particular service mesh. By native, I mean it’s actually built on the proxy that Istio is built on, and provides the various capabilities that you will likely need at the edge. Things like transformation. Things like data loss prevention, web application firewalling, maybe even things like SOAP translation. Things that gateways can do today, but now you can pull this and make it native into the service mesh instead of trying to hack together something that you’re going to have to maintain around your existing gateways.
Global Service Routing, Failover, and Continuity across Infrastructure
Then there’s the point around, deploy across multiple clusters, how services find each other across multiple clusters. Then building a highly available service-to-service communication fabric. Basically, it comes down to what you did in the past. Just set up a bunch of hardware load balancers, and the load balancer when you curl it, will spread the curl into a pool of services. That incurs additional expense. That incurs additional hops in the network. It might be more worthwhile to instead of forcing everything out of a cluster back through gateway, into the cluster, and then back out again when services need to talk with each other, the ability to talk directly to each other when it makes sense. To be smart enough to know how to route and how to fail over without having to rely on some external and expensive load balancers. Something more like this, where traffic from app A can go to app B, even across failure domains without having to cross back through some centralized load balancer.
Workload Certificate Management Integration with Existing PKI
Another really big topic when it comes to adopting and operating a service mesh in these organizations is, how do we solve for the certificate management problems when we’re talking about enabling mutual TLS? That’s one of the benefits of using a service mesh at layer 7, where applications are communicating with each other. We can assign identity to the applications. Encode that identity in the transport, using certificates. Then apply policies to those identities. Policy is about whether A is allowed to talk with B. To do this, the underpinnings of an implementation like this right now depend on certificates. You will likely want to tie that back into your own PKI, Public Key Infrastructure. You might have Vault. You might be using one of the cloud CAs or something like that, and safely doing this. Because you don’t want to start handing out intermediate signing CAs, or root CAs, or any of this stuff into your infrastructure without keeping things extremely secure. This is definitely an area where, first of all, don’t write things to disk. Don’t put things in secrets. Keep things in memory. Offload root CA handling to some offline hardware management. These are all compatible practices when deploying a service mesh. Getting this right is extremely important.
Extending the Service Mesh
One of the last pieces that I’ll cover is actually extending the service mesh. The proxies are on the request path in the mesh, and they can be configured with the control plane. The proxies have a set of capabilities that are coded into the proxy that you can use or not use. You might need a customization to fit maybe what your organizations are already doing. Typically, what we’ve seen here at Solo is that those customizations are around security, like you were trying to retrofit the mesh into a brownfield environment where services are already communicating with each other. They have some existing security protocol, maybe they’re parsing some token or signature, and you have to verify that maybe it’s not using JWT or some accepted practice, or something that was built 10 years ago, and you need to be backward compatible with that.
At Solo, one of the things we’ve been excited about for a while now, and we’ve seen adoption of, is WebAssembly to extend the capabilities of the proxy, and do that dynamically. You can write your security plugin in WebAssembly, and then inject that into the proxies, where it makes sense, the applications that care about that, and dynamically alter the behavior of the mesh. This is extremely important and a versatile way of getting that last 10% or that last mile fit for your organization’s use cases by making the customizations yourself. Without having to dig into Envoy proxy, and C++, and managing a build of Envoy, and basically forking Envoy, maintain your own build. You can use WebAssembly to do that, which is pretty powerful.
Integrating VMs into the Mesh
There’s actually one more really important concept that comes up when deploying a service mesh into the enterprise, and that is a lot of the meshes can run nicely on Kubernetes, which is containerized workloads. A lot of their workloads actually run on VMs, and we need a way to integrate those VMs into the mesh, so either deploying the sidecar or using some gateways to integrate the VMs into the service mesh. Different mesh providers have different level of support for this. Things like Consul from HashiCorp started off in that generation of technology on the VMs, and then are slowly trying to inch into Kubernetes. You have people like Linkerd who are not doing anything with VMs. Then you have Istio, which is in the middle that was Kubernetes first, but not only, and offers support for integrating VMs as first class citizens into the mesh. That’s a very important piece of the puzzle when adopting a service mesh.
Demo
Let’s go back to a big use case. I like to say that people don’t want a service mesh, but they have needs around consistent policies, failover, high availability, compliance requirements, and so on. A service mesh can be used to solve that. Let’s take a look at an example and a demo that I’ll show around an architecture that illustrates, or mimics something that you might want to do in a multi-cluster setup. In this case, we have two different clusters: one in the West region, one in the East region. We also have a third cluster at the bottom that is our Gloo Mesh management controllers, which automates the configuration federation of multiple clusters.
Then on the top part of the diagram, we have another cluster with API gateways that are built on Istio. Basically, there’s another multi-cluster Istio scenario, but the API gateways can do things like rate limiting, and web application firewalling, request transformation, invoking AWS Lambdas, these things directly. Traffic flows through them into the clusters. Then when traffic is in the clusters and in the mesh, then we can apply these failover policies. Everything looks transparent when failing over and maintaining continuity, whether you’re calling from the outside of the mesh, or whether you’re a client inside the mesh. Let’s go and take a quick look at that.
Here, what we’re going to see is we are outside the mesh, we’re calling from my laptop, a curl command to a set of services that will go through the gateway. The name will get resolved using external DNS. Nothing’s super special about this. The curl will go through the gateways into an app called Web API, which then curls recommendation, which then curls purchase history. There’s a graph of curls, a sequence of curls here. If things fail over or stop working in this cluster, then we should be able to fail over without going back through the API gateways, directly between clusters. Let’s see how that works.
In this particular curl, it looks like the DNS routed me to cluster 2. That’s fine. Curl it a couple more times, looks like I got cluster 2 again. Now I got cluster 1. Curl it a few more times, we see externally, we land on one of the cluster that’s actually closest to me, and it happens to be the West cluster, and that’s cluster 1. One thing we’ll notice is that we are calling the global names, whether that is externally here from my laptop, or internally within the service mesh, we’re calling global names. We don’t want to pin ourself to topology specific names, Kube DNS. What we want to use is global names to deploy the apps, so when they are running inside the mesh they behave a certain way, when they run outside of the mesh, they behave a certain way. The apps don’t know and they don’t care, and they shouldn’t.
On the top pane, we see cluster 1, which has Web API, which curls recommendation, which curls purchase history. On the bottom pane, we see cluster 2, same thing. If I come back here to cluster 1, I go into a sleep pod or client here, and I do a curl on web API service, we will see the response, and it will come. We can see the full response. Again, we’re calling the global name, and it’s going into cluster 1. It will always go into cluster 1, and it will stay in cluster 1 unless there’s some failover event. We won’t see the load balancing like we did when I was calling from my laptop. Another thing to notice is if I do a little bit more verbose curl here, when I did this curl here, we are resolving to an IP that is not a public gateway. It’s not a public address. It is an internal mesh-only address. We’re not going out back through the API gateways for this curl. We’re going from the client, which is a mesh, to the web API service, which is also in the mesh directly. Right now we let the service mesh apply its policies for that communication.
The last thing that I’ll show here is if I take down the purchase history replica running in this cluster. We take that down, that becomes zero replicas. We come back to the client in the mesh, and we make a curl to the Web API service. We’ll notice that the curl ended up in cluster 1 like we expected. What we have there actually is locality we’re routing, and then when it hits the purchase history service, it will actually fail over to cluster 2, automatically and transparently. Again, we’re calling the global name, purchase history, and the application network is responsible for implementing the various failover and priority, and sometimes regulatory policies about how traffic should flow through the system. In this case, we correctly fail over to cluster 2.
Summary
At Solo, we are the leaders in this space. We’re working with probably the largest deployments of service mesh in the world. It is a great place to work, to learn, to contribute to open source, to contribute to the ecosystem and the industry in general around this space. We’re all over the world. It doesn’t matter where you’re located.
Questions and Answers
Losio: First of all, I’ll start with a question that has the chicken and egg problem, that is, you start with some microservices. You have something at the beginning. When should you really start to think about the service mesh? I’m a new startup. I have a new made project or whatever. I have something already running or I’m slowly growing. I have high hopes, but when is the tipping point?
Posta: It first starts off with your microservice journey in general. Building a system as a set of services that are communicating over the network, and you plan on adding more, that by itself is already a fairly complicated situation. You need to have the supporting infrastructure to be able to run that and to be able to operate that going forward. The first things that you want to consider, in that scenario, are probably not service mesh. They’re probably things like, how do we deploy these? Where do we deploy them? How are the teams going to make updates to them? How do we build a process to enable self-service, because a big part of why you’re likely building microservices is to be able to move faster. Those are some of the initial things that you want to consider.
You also have to factor in the rate of either learning or adoption. How comfortable an organization is with building those pieces out first? You don’t want to try to do everything all at once, because that’s not going to be very fruitful. You have to consider, who’s driving this in the organization? Is it the developers? Is it bottom up? Is it the executives? Is it top down? Is it somewhere in the middle? All of these things contribute? Once you get that stuff sorted out, and you figure out, how am I going to bring 2, 3, 5 microservices into a working environment? Then you have to worry about and consider the network. That problem will never go away. When you’re talking about microservices, you’re putting things on the network. You’re putting request, response. You have to deal with the realities of the network, front and center.
If you happen to be adopting something like Kubernetes, some of that stuff, Kubernetes does start helping with some of those things. If a service goes down, Kubernetes will try to bring it back up. If you are trying to look for some basic service discovery, Kubernetes has stuff like that. You might be able to get something out of your platform, even if it’s just a core bare bones platform already that you should consider as a step in that direction. There are other things like if you have a small number of services, where it might make sense to look at a gateway, a more modern edge gateway, ingress gateway, API gateway. Actually, the way a lot of people start with something like Istio is to deploy the ingress gateway first, and start operationalizing those pieces and use that for some basic routing, and then start to tiptoe into, let’s start exploring how sidecars work for my application. There’s no hard and fast rules here. There are areas that you want to consider. Have some foundational infrastructure in place first to support microservices. Then think about the growth of the platform. How you’re going to operate it. For some teams that might be, yes, you look at service mesh right away, because maybe they’re already familiar with Kubernetes. Maybe they already have CI/CD. Maybe they have their security pipelines and scanning, and all that stuff all set up. Now they’re just trying to spin up a new set of apps.
Losio: You see that as an easier transition at that point. It really depends as well. As you mentioned this already, with a single digit number of services, you may already have a very good use case to move to, or definitely start to work with.
Is something that is just a service mesh just something for microservices? How do you see that?
Posta: I think anything that communicates over the network could tend to benefit from what the service mesh is doing. It just happens to be that for a larger scale services environment, where communication over the network has become more proliferated, then a service mesh brings more value in those environments. If you just have one monolith, then maybe less so. Maybe a simple gateway will be useful there. The more things you have communicating over the network, which in today’s IT age, that’s becoming more, even to the extent that you scale out to IoT. The network is being highly leveraged here. Then the last piece is the type of infrastructure that you’re deploying too as well. Let’s say you have 10 physical boxes, machines, and you’re deploying applications on 10 of those, it’s not a very dynamic environment. You’re starting to use a network so you still need to solve these network concerns. If the infrastructure is not all that dynamic, applications are not changing, and so on, then maybe a gateway would be sufficient for something like that. If you see that the infrastructure applications could be becoming healthy, unhealthy, going away completely, scaling, autoscaling, then that adds another element, another variable that exacerbates the problems around the network.
Losio: How do you implement observability on a service mesh, or how will you integrate what you have as well, in terms of observability?
Posta: Observability is a property of a system, first of all. Let’s start off with that. What that means is observability has to be taken into account at all levels of the system. What you want to build an observable system for, why you want to do that, is so that when things go wrong, you can start asking questions, pull back the onion and figure out what’s happening, and have enough data to be able to do that. That’s an observable system. The service mesh is playing on the layers of the network, between the applications at the application level, so it’s looking at HTTP requests. It’s looking at application layer protocol and request. It plays a part in that observability story. Typically, how people are integrating the mesh with the rest of the story is by starting off, at least with what are the top-line application to application networking metrics that you might be interested in? Things like, how many requests are going from service A to B?
Losio: High level request and high level metrics, so start from there.
Posta: Throughput, latency, error rates, saturation, these four or five top level important metrics that you might want to capture between services. You can also do things like distributed tracing, capturing access logs, and these types of things. Then you want to pull that back into your larger system, and use that for observability.
The NoSQL market report is a perfect analysis that can provide you with an elaborate study of the NoSQL market. You will not need to worry about knowing your niche with this carefully crafted market analysis. The report will provide perceptive data about all the channels related to your domain as it covers different demographics and geographical regions across the globe related to NoSQL market. The report contains data about key market players, predicted size of the market, statistics to inform about where opportunities lie, competitor analysis and vendor information. The future trends and current restraints will aid in making strategic decisions.
The NoSQL market report will provide forecasts based on real figures and factual data to help you decide on your marketing plans. You will understand which are the key profit making sectors with the broad picture presented in the report. You can then leverage these opportunities based on your developed strategies and grow stronger in the market. The information is gathered from real-time sources such as customers, dealers, suppliers of raw materials and so on. Due to this, the data gathered is authentic and will provide complete details of the NoSQL market.
NoSQL Market: Competitive Landscape
The NoSQL market report includes information on the product launches, sustainability, and prospects of leading vendors including: (SAP, MarkLogic, IBM Cloudant, MongoDB, Redis, MongoLab, Amazon Web Services, Basho Technologies, Google, MapR Technologies, Couchbase, AranogoDB, DataStax, Aerospike, Apache, CloudDB, MarkLogic, Oracle, RavenDB, Neo4j, Microsoft)
NoSQL market is split by Type and by Application for the period 2021-2028, the growth among segments provides accurate artifices and forecasts for sales by Type and by Application in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.
By Top Key Players
SAP MarkLogic IBM Cloudant MongoDB Redis MongoLab Amazon Web Services Basho Technologies Google MapR Technologies Couchbase AranogoDB DataStax Aerospike Apache CloudDB MarkLogic Oracle RavenDB Neo4j Microsoft
By Types
Key-Value Store Document Databases Column Based Stores Graph Database
By Applications
Retail Online gaming IT Social network development Web applications management Government BFSI Healthcare Education Others
NoSQL Market: Regional Analysis
All the regional segmentation has been studied based on recent and future trends, and the market is forecasted throughout the prediction period. The countries covered in the regional analysis of the Global NoSQL market report are U.S., Canada, and Mexico in North America, Germany, France, U.K., Russia, Italy, Spain, Turkey, Netherlands, Switzerland, Belgium, and Rest of Europe in Europe, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, China, Japan, India, South Korea, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), and Argentina, Brazil, and Rest of South America as part of South America.
Overview: Along with an expansive outline of the worldwide NoSQL market, this segment gives an outline of the report to give a thought regarding the nature and substance of the examination study.
Analysis of Strategies of Leading Players: Market players can use this analysis to gain a competitive advantage over their competitors in the NoSQL market.
Study on Key Market Trends: This piece of the report offers a more significant assessment of the latest and future examples of the market.
Market Forecasts: Buyers of this report will approach precise and approved evaluations of the all market size as far as worth and volume. The report additionally gives utilization, creation, deals, and different conjectures for the NoSQL market.
Local Growth Analysis: All critical regions and countries have been covered in the report. The neighborhood examination will help with elevating players to exploit dismissed common business areas, prepare express philosophies for target regions, and contemplate the improvement of each and every regional market.
Segmental Analysis: The report gives precise and solid conjectures of the piece of the pie of significant portions of the NoSQL market. Market members can utilize this examination to make key interests in key development pockets of the market.
What will be the development pace of NoSQL market?
What are the key factors driving the Global NoSQL market?
Who are the key manufacturers in the market space?
What are the openings, hazards, and outline of the market?
What is sales, revenue, and price analysis of top manufacturers of NoSQL market?
Who are the distributors, traders, and dealers of NoSQL market?
What are the NoSQL market opportunities and threats faced by the vendors in the Global NoSQL industries?
What are deals, incomes, and value examinations by types and utilizations of the market?
What are deals, income, and value examinations by areas of enterprises?
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Global Document Databases market 2022 published by Global Market Vision, starts with market description, executive report, segmentation, and classification. The report offers a comprehensive analysis of the market so that readers can be guided about future opportunities and high-profit areas of the industry. The report provides a detailed analysis of the market structure considering the current market landscape, Leading Industry Share, upcoming market trends, leading market players, product type, application, and region.
Development policies and plans are discussed, and manufacturing processes and industry chain structures are analyzed. This report also gives the import/export, supply, and consumption figures, as well as manufacturing costs and global revenues, and gross margin by region. Numerical data is backed up with statistical tools such as SWOT analysis, BCG matrix, SCOT analysis, and PESTLE analysis. Statistics are presented in graphical form to provide a clear understanding of the facts and figures.
To define, describe, and forecast the 2028 Market by segments, and region
To provide detailed information about the major factors (drivers, restraints, opportunities, and challenges) influencing the growth of the market
To analyze the sub-segments with respect to individual growth trends, prospects, and contributions to the total market
To analyze opportunities in the market for stakeholders and provide the competitive landscape of the market
To forecast the revenues of the market segments with respect to the major regions, such as North America, Europe, Asia Pacific (APAC), Middle East & Africa, and South America
To profile the key players and comprehensively analyze their recent developments and positioning in the virtual sensors market
To analyze competitive developments, such as mergers and acquisitions, new Company developments, and Research and Development (R&D) activities, in the market
COVID-19 Impact
Report covers Impact of Coronavirus COVID-19: Since the COVID-19 virus outbreak in December 2019, the disease has spread to almost every country around the globe with the World Health Organization declaring it a public health emergency. The global impacts of the coronavirus disease 2019 (COVID-19) are already starting to be felt, and will significantly affect the Retro Scooters Market in 2022.
The outbreak of COVID-19 has brought effects on many aspects, like flight cancellations; travel bans and quarantines; restaurants closed; all indoor/outdoor events restricted; over forty countries state of emergency declared; massive slowing of the supply chain; stock market volatility; falling business confidence, growing panic among the population, and uncertainty about future.
Reasons to Purchase the report:
This report provides insights into the global Document Databases Market along with the latest market trends and future forecasts to illustrate the future investment pockets.
The potential of the global Document Databases Market is determined by understanding the effective trends to increase the company’s position in the market.
This market report provides insights and detailed impact analysis on key influencers, constraints and opportunities.
Five Porter strengths analysis to demonstrate the strengths of suppliers and buyers.
The latest developments, market shares and strategies used by key market players
Table of Content:
Chapter 1: Introduction, market driving force product Objective of Study and Research Scope Document Databases market
Chapter 2: Exclusive Summary – the basic information of Document Databases Market.
Chapter 3: Displaying the Market Dynamics- Drivers, Trends and Challenges of Document Databases
Chapter 5: Displaying the by Type, End User and Region 2015-2020
Chapter 6: Evaluating the leading manufacturers of Document Databases market which consists of its Competitive Landscape, Peer Group Analysis, BCG Matrix & Company Profile
Chapter 7: To evaluate the market by segments, by countries and by manufacturers with revenue share and sales by key countries in these various regions.
Chapter 8 & 9: Displaying the Appendix, Methodology and Data Source
Conclusion: At the end of Document Databases Market report, all the findings and estimation are given. It also includes major drivers, and opportunities along with regional analysis. Segment analysis is also providing in terms of type and application both.
If you have any special requirements, please let us know and we will offer you the report at a customized price.
About Global Market Vision
Global Market Vision consists of an ambitious team of young, experienced people who focus on the details and provide the information as per customer’s needs. Information is vital in the business world, and we specialize in disseminating it. Our experts not only have in-depth expertise, but can also create a comprehensive report to help you develop your own business.
With our reports, you can make important tactical business decisions with the certainty that they are based on accurate and well-founded information. Our experts can dispel any concerns or doubts about our accuracy and help you differentiate between reliable and less reliable reports, reducing the risk of making decisions. We can make your decision-making process more precise and increase the probability of success of your goals.
Team-set salaries can be used to set fair compensation for individuals in multiskilled, collaborative, autonomous teams. People don’t appraise themselves, only their colleagues. It gives everyone a direct say in salary settings.
With team set salaries (TSS), appraisals are made by team members themselves in about 15 minutes, using the zero-sum metaphor of “dividing up a pie”. This means that team members cannot simply give everybody else a good review, as they could in traditional 360 reviews, as Wuestefeld explained:
When you say some colleague will get a larger chunk of the pie, automatically all others get a smaller chunk.
Some people fear this “zero-sumness” as taboo, but it simply embraces the finite reality of a compensation budget at any given point in time, Wuestefeld mentioned.
TSS requires people to do their appraisals by answering a single overarching question. The question Wuestefeld uses is “What is the value of each person’s contribution compared to their colleagues?” This allows his team to collaboratively resolve the subjectivity that is inherent to the appraisal of any kind of teamwork:
TSS results tell me precisely how much of the compensation “pie” each person should get, in the team’s collective opinion. “Ann should get 13.6% of the pie and Bob should get 10.2%”, for example. So, when I have a new budget for giving people raises, I give them to the people deserving them the most, according to TSS results.
“As a manager, I still have the final say on compensation, but I have found the raw TSS results to be consistently fair over the years,” Wuestefeld mentioned, “they represent each team’s collective opinion after all.”
InfoQ: How do team-set salaries differ from traditional reviews?
Klaus Wuestefeld: With traditional 360-degree reviews, team members have to spend hours filling in review forms in a process that quickly decays into a popularity contest. People are discouraged from giving an honest negative review in fear of retaliation, so the whole thing becomes a political exchange of favourable reviews.
Managers are then forced to spend days in secretive, closed-doors “calibration” meetings, to arbitrate people’s results. Calibration meetings are where transparency goes to die. It’s no wonder that everyone, managers especially, hates traditional performance reviews.
InfoQ: What challenges have you seen when working with team-set salaries? How did you deal with them?
Wuestefeld: An employee once complained that the process was “too impersonal” because the final result that balances all appraisals is produced by an algorithm. People who get bad results in TSS – or any process, really – will sometimes complain about the process rather than owning the problem and seeking to improve.
That is actually a problem that I WANT to have. I want the people with bad results to become uncomfortable and give the team feedback, so we can improve our working system, or voluntarily switch jobs to some other company where they can thrive.
InfoQ: What benefits did you get?
Wuestefeld: Performance review and compensation setting used to be quite stressful. I used to have people knocking on my door, demanding raises every other week. Even trying to be 100% fair and holding calibration meetings with respected senior employees, people would perceive the process for what it was: non-transparent and arbitrary.
Using TSS, performance appraisal for salary setting became a non-issue in my teams; something that happens naturally, in 15 minutes every quarter. The perception of fairness and transparency is 100%.
About the Author
Ben Linders
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The latest market research report analyzes NoSQL Market demand by Different segments Size, Share, Growth, Industry Trends and Forecast to 2028 in its database, which describes a systematic image of the market and provides an in-depth explanation of the various factors that are expected to drive the market growth. The universal NoSQL market research report is the high-quality report having in-depth market research studies. It presents a definite solution to obtain market insights with which market place can be visualised clearly and thereby important decisions for the growth of the business can be taken. All the data, facts, figures and information covered in this business document is backed up by well renowned analysis tools which include SWOT analysis and Porter’s Five Forces analysis. A number of steps are used while preparing NoSQL report by taking the inputs from a dedicated team of researchers, analysts and forecasters.
The projected sale of a product is also included in this NoSQL market report, which aids market participants in bringing new product releases to market and avoiding errors. It suggests which parts of the business should be enhanced in order for the company to be prosperous. It is also simple to discover a new chance to keep ahead in the market, and this market study report gives the most recent trends to assist you in placing your company in the market and gaining a significant benefit.
The NoSQL Market report has been segregated based on distinct categories, such as product type, application, end user, and region. Each and every segment is evaluated on the basis of CAGR, share, and growth potential. In the regional analysis, the report highlights the prospective region, which is estimated to generate opportunities in the global NoSQL market in the forthcoming years. This segmental analysis will surely turn out to be a useful tool for the readers, stakeholders, and market participants to get a complete picture of the global NoSQL market and its potential to grow in the years to come.
Covid-19 Impact Outlook
This section of the report reveals the consequence of the covid pandemic on business, globally. Effect on manufacturing activities, production, demand, supply chain and logistics management, and distribution networks has been exposed in this report. The analysts have pointed out the measures or strategies that the companies are taking up to fight the covid-19 impact. Moreover, they have identified key opportunities that are emerging post-COVID-19. This will help the players capitalize on the opportunities to recover losses and stabilize their businesses
Why to Buy this Report?
For getting the detailed analysis of business strategies regarding the major key players which are already existing in the global NoSQL market along with value chain, raw material, and industry variable.
To understand all the information related to NoSQL market according to its market, segmentations and sub-segmentation.
Report gives in-depth research on distribution channels and distribution chain with retailers, wholesalers, manufacturers, dealers, suppliers, and consumers.
Report covers all the factors such as CAGR, supply and demand, macroeconomic patterns, customer purchasing patterns, and several other with proper and authentic data.
Also, with the help of SWOT analysis, PESTLE analysis, and opportunity assessment researchers and analysts offers the accurate and verified information through the report.
Major Points Covered in TOC:
Market Overview: It incorporates six sections, research scope, significant makers covered, market fragments by type, NoSQL market portions by application, study goals, and years considered.
Market Landscape: Here, the opposition in the Worldwide NoSQL Market is dissected, by value, income, deals, and piece of the pie by organization, market rate, cutthroat circumstances Landscape, and most recent patterns, consolidation, development, obtaining, and portions of the overall industry of top organizations.
Profiles of Manufacturers: Here, driving players of the worldwide NoSQL market are considered dependent on deals region, key items, net edge, income, cost, and creation.
Market Status and Outlook by Region: In this segment, the report examines about net edge, deals, income, creation, portion of the overall industry, CAGR, and market size by locale. Here, the worldwide NoSQL Market is profoundly examined based on areas and nations like North America, Europe, China, India, Japan, and the MEA.
Application or End User: This segment of the exploration study shows how extraordinary end-client/application sections add to the worldwide NoSQL Market.
Market Forecast: Production Side: In this piece of the report, the creators have zeroed in on creation and creation esteem conjecture, key makers gauge, and creation and creation esteem estimate by type.
Research Findings and Conclusion: This is one of the last segments of the report where the discoveries of the investigators and the finish of the exploration study are given.
If you have any special requirements, please let us know and we will offer you the report as you want.
About Global Market Vision
Global Market Vision consists of an ambitious team of young, experienced people who focus on the details and provide the information as per customer’s needs. Information is vital in the business world, and we specialize in disseminating it. Our experts not only have in-depth expertise, but can also create a comprehensive report to help you develop your own business.
With our reports, you can make important tactical business decisions with the certainty that they are based on accurate and well-founded information. Our experts can dispel any concerns or doubts about our accuracy and help you differentiate between reliable and less reliable reports, reducing the risk of making decisions. We can make your decision-making process more precise and increase the probability of success of your goals.
Couchbase Mobile is the Santa Clara, Calif.-based vendor’s technology intended for mobile and embedded devices. With the new release, Couchbase now supports edge computing deployments in an approach that can integrate with a Couchbase database running in the cloud.
“Edge computing has emerged as a necessary complement to cloud for mobile applications that are sensitive to network latency and availability,” IDC analyst Dave McCarthy said.
Bringing Couchbase Mobile 3 and NoSQL to the edge
The focus for the new Couchbase Mobile release is to help developers build out distributed applications that span from edge to cloud.
Edge computing has emerged as a necessary complement to cloud for mobile applications that are sensitive to network latency and availability. Dave McCarthyAnalyst, IDC
McCarthy noted that Couchbase Mobile 3 enables developers to deploy a full-featured NoSQL database-to-edge infrastructure. He added that the deployment on edge devices can then be integrated to the cloud with the Couchbase Sync Gateway, a data synchronization server.
Meanwhile, enterprise application development today is being driven by large market trends, said Wayne Carter, vice president of engineering at Couchbase.
The key trend is device expansion, driven in large part by the rise of 5G technology, which brings more capabilities for mobile and edge deployments.
“There’s a rush to all-digital engagement fueled by 5G technology, and this has led to a dramatic increase in the number of users and the types of devices that need an embedded database,” Carter said.
The move to the edge of the network is another trend that is influencing application development. Carter noted that developers are increasingly moving data and compute resources closer to where the resources are being used.
The trend toward the edge is creating momentum toward delivering applications faster to users, Carter added.
How Couchbase Mobile 3 eases NoSQL database edge management
The vendor’s main focus with Couchbase Mobile 3 was making it easier for users to manage edge deployments. Organizations can deploy Couchbase in a variety of complex approaches where their databases are spread over multiple locations.
For example, Carter noted that an organization could have several physical locations with Couchbase Mobile deployed in each environment. Each of the individual databases needs to be managed and configured, and they might also need to be able to synchronize with a central database server running in the cloud.
The Couchbase Mobile architecture now enables distributed NoSQL database deployments from the edge of the network into the cloud.
To help enable the management of edge-to-cloud types of deployments, Couchbase now has a secure administration feature as part of the Couchbase Sync Gateway. The feature enables secure management of cloud and edge environments, and provides the ability to centrally update large clusters.
Couchbase has also certified its Couchbase Mobile technology for edge computing technology services from AWS, including the AWS Wavelength and AWS Local Zones edge services.
“Customers that deploy out to the edge or deploy in the cloud can now use the same set of tools from AWS,” Carter said. “The database at the edge and in the cloud is the same, and users get that from Couchbase.”
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MongoDB, Inc. (NASDAQ:MDB – Get Rating) was the target of some unusual options trading activity on Wednesday. Traders purchased 36,130 call options on the company. This represents an increase of 2,077% compared to the average volume of 1,660 call options.
Shares of MongoDB stock opened at $354.81 on Thursday. The stock has a market capitalization of $23.68 billion, a P/E ratio of -75.01 and a beta of 0.80. The company has a quick ratio of 4.75, a current ratio of 4.75 and a debt-to-equity ratio of 1.71. The company has a 50-day simple moving average of $437.09 and a 200 day simple moving average of $464.07. MongoDB has a 12-month low of $238.01 and a 12-month high of $590.00.
MongoDB (NASDAQ:MDB – Get Rating) last posted its quarterly earnings data on Monday, December 6th. The company reported ($0.11) earnings per share for the quarter, beating the consensus estimate of ($0.38) by $0.27. The firm had revenue of $226.89 million during the quarter, compared to analysts’ expectations of $205.18 million. MongoDB had a negative net margin of 38.32% and a negative return on equity of 101.71%. The company’s quarterly revenue was up 50.5% compared to the same quarter last year. During the same quarter last year, the company posted ($0.98) EPS. On average, equities analysts anticipate that MongoDB will post -4.56 earnings per share for the current year.
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In other MongoDB news, CFO Michael Lawrence Gordon sold 5,000 shares of the stock in a transaction on Wednesday, December 22nd. The shares were sold at an average price of $552.19, for a total value of $2,760,950.00. The sale was disclosed in a filing with the Securities & Exchange Commission, which can be accessed through the SEC website. Also, CEO Dev Ittycheria sold 33,692 shares of the stock in a transaction on Thursday, February 10th. The shares were sold at an average price of $449.01, for a total transaction of $15,128,044.92. The disclosure for this sale can be found here. Insiders sold a total of 171,864 shares of company stock worth $78,398,007 over the last quarter. 7.40% of the stock is currently owned by company insiders.
A number of institutional investors and hedge funds have recently bought and sold shares of MDB. Price T Rowe Associates Inc. MD increased its position in MongoDB by 191.2% in the 2nd quarter. Price T Rowe Associates Inc. MD now owns 5,766,896 shares of the company’s stock valued at $2,084,848,000 after acquiring an additional 3,786,467 shares in the last quarter. Allspring Global Investments Holdings LLC acquired a new stake in MongoDB in the 4th quarter valued at about $674,390,000. Moors & Cabot Inc. acquired a new stake in MongoDB in the 3rd quarter valued at about $601,000. TD Asset Management Inc. increased its position in MongoDB by 153.9% in the 4th quarter. TD Asset Management Inc. now owns 525,000 shares of the company’s stock valued at $277,909,000 after acquiring an additional 318,259 shares in the last quarter. Finally, Growth Interface Management LLC acquired a new stake in MongoDB in the 3rd quarter valued at about $86,758,000. Hedge funds and other institutional investors own 89.57% of the company’s stock.
MDB has been the subject of a number of analyst reports. Stifel Nicolaus raised their price objective on shares of MongoDB from $495.00 to $550.00 and gave the stock a “buy” rating in a report on Tuesday, December 7th. Needham & Company LLC raised their price objective on shares of MongoDB from $534.00 to $626.00 and gave the stock a “buy” rating in a report on Tuesday, December 7th. Barclays reduced their price objective on shares of MongoDB from $590.00 to $556.00 in a report on Wednesday, January 12th. raised their price objective on shares of MongoDB from $475.00 to $560.00 and gave the stock a “buy” rating in a report on Tuesday, December 7th. They noted that the move was a valuation call. Finally, The Goldman Sachs Group raised their price objective on shares of MongoDB from $475.00 to $545.00 and gave the stock a “buy” rating in a report on Wednesday, December 8th. One analyst has rated the stock with a sell rating, three have given a hold rating and thirteen have issued a buy rating to the company. According to MarketBeat, the company has a consensus rating of “Buy” and an average price target of $542.00.
MongoDB, Inc engages in the development and provision of a general purpose database platform. The firm’s products include MongoDB Enterprise Advanced, MongoDB Atlas and Community Server. It also offers professional services including consulting and training. The company was founded by Eliot Horowitz, Dwight A.
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Before you consider MongoDB, you’ll want to hear this.
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While MongoDB currently has a “Buy” rating among analysts, top-rated analysts believe these five stocks are better buys.
MongoDB, Inc. (NASDAQ:MDB – Get Rating) was the target of some unusual options trading activity on Wednesday. Traders purchased 36,130 call options on the company. This represents an increase of 2,077% compared to the average volume of 1,660 call options.