Around 100 people in my company use Vertica.

The solution is easy to scale.

We have seven people using the solution.

It is scalable. You just add extra nodes. But like all data solutions and all databases, you have to always consider how the data is stored, and how the data is queried. We have Elasticsearch and several other database. They will perform differently when used for different tasks. The right database for the right task.

Vertica is really quick, but with poor query design a report can take far too long. 
Vertice EON mode allows for true user / query type scalability by firing up additional clusters as requirements change

Vertica is a scalable solution.

I would rate the scalability an eight or nine out of ten based on the use case that we do.

We are a team that handles operational reporting, and our Vertica implementation is used by thousands of people. However, the team responsible for managing and writing code for Vertica consists of only around ten to twelve people.

I have not encountered any scalability issues.

Vertica is scalable.

Scalability has been amazing. We have seen a lot of improvement. We have developers and we have a production demo. We have hosted clusters for customers, we have deployed customer scope. I can scribe them by petabytes. I can scale them by the number of users. It depends on the customers. For one project we can have 15 to 20 consecutive users, but they deal with petabytes of storage.

No issues. Amazingly scalable.

Adding one node was very easy, as was adding memory to all nodes. We are currently in the process of setting up a Dev / DR environment which is going very smoothly.

The scalability of Vertica is good.

We have approximately 100 users using this solution.

It is a scalable solution. Initially, we had issues with the scalability, but with the new version, Vertica resolved the issues.

Regarding how many users are using this solution, I do not have a specific number, but our organization is large. So, for example, in a unit with about fifteen clients, two to three clients use Vertica.

We've had no issues scaling it.

None.

Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down.

We have approximately 25 people using this solution in my company. Most of the users are developers. We have been increasing usage of the solution.

Vertica is a scalable solution.

We had an issue caused by adding nodes, but this error was caused by ourselves, as we didn’t use the proper process for adding nodes. That led to some problems that needed to be solved. Even though we did something bad, the instance was still working properly from an outside point of view.

Scalability is great if you size it correctly to start with. Resizing a cluster isn’t for the faint of heart. All the data needs to be redistributed across the cluster when the cluster size changes, and that can take a very long time, depending on how much data you’re storing.

We haven’t yet scaled out our system. So far performance has been good (taking into consideration that delete strategy mentioned in the Areas for Improvement question).

This is a scalable solution. 

This is a scalable solution. For example, if we look at Uber drivers, they are able to monitor the position and availability of the drivers and match that against the number of customers for every customer and every driver worldwide globally.

They do a geospatial analysis and calculate their search pricing. They are defined by geographical boundaries, they are defined by where the people are and where the drivers are. This is done for every city in the world for every driver. That gives you an idea of the scale they are able to do in this particular use case.

This gives you the idea of the scale, the performance, and the ability to do analytics in the database. They do this so much more cost-effectively than they would on any other platform.

With the Community Edition we are restricted to three nodes. We have a lot of enterprise clients who stress our cluster to its limits. The only advice I would give to new adopters is that if you want superior performance and reliability you are better off going all-in with the enterprise edition and a large number of nodes; assuming you have a lot of clients who run queries concurrently.

No scalability issues. Like I said, in its competitive set it is just faster, better, depending on how you use it, because it is columnar.

We have had no issues scaling it for our needs.

Scalability is one of the huge strengths of this product, and scalable in a way, as I said before, that is native to how we do business.

Vertica is massively scalable. My customers' workloads vary. While the number of users is not necessarily the ideal performance measure, the user bases range from a few dozen in smaller setups to thousands in the largest setups. And some of my customers have several hundred users on the platform concurrently.

Our DB isin in the tens of Gigs, we did not need to scale yet.

This is a scalable solution. 

The solution has great scalability. We started with one terabyte of compressed data, this is a lot of data and we never had problems with the scalability. You can have hundreds of terabytes with the solution if you want, it all depends on your needs.

I have not encountered any scalability issues; I think it's scalable.

No.

The reason we like Hadoop and others is because they scale up, pricing doesn't scale up at the same level. Vertica is a license per terabyte product. They do give you discounts the more volume you get, but it adds up over time fast. We could scale at a lower cost with than other solutions.

Scaling was a pain point. Getting recommendation on how to set it up ultimately to provide the best performance, how many notes, other things. We got different answers from them.

We've had no issues scaling it.

I have not encountered any scalability issues.

Scalability was a problem given we had to host the solution ourselves. It would be great to have a cloud-based solution around Vertica. Also, we found it difficult to modify and update our schema as we grew. Part of the problem may have been that when we first started using Vertica we were inexperienced.

Suboptimal projection design causes queries to not scale linearly.

The metadata layer does not scale linearly.

Metadata for database files scale okay, but metadata related to tables/columns/sequences must be stored on all nodes.

We have been able to scale it for our needs.

No.

No

We did not encounter hardly any scalability issues.

There have not been any scalability issues. We are able to support trillions of data elements by adding more servers.

No

None

None

I have found the solution to be scalable.

The default layout (all nodes running spread) introduces latencies in query planning when you reach about 60 nodes, in our experience. Switching to a large cluster (one control node per rack) would be advised, way before reaching the 128 nodes hard limit.

Before using Vertica, we used to have problems scaling out because we increase our customer base significantly each year. We have more than 20.000 clients now. Since we implemented the Vertica solution, it is much less effort to maintain scalability.

We can scale a lot, wish it was a bit more affordable.

Depends on the environment. Generally pretty good. If you have a large catalog, you can get timeouts adding nodes. Large catalog issues have been dealt with it recent releases so this should make scaling up even more robust.

Not yet

None.

Not yet.

No

There were no scalability issues.

No, scalability is also a strength of the solution.

It has an elastic scalability solution.

It is very easy to scale Vertica as you need.

No scalability issues.

Concurrency

There have been no issues scaling it for our needs.

Rebalancing after adding nodes is an issue in terms of resources and especially locking of tables. It would be nice if this could be more transparent.

We did not encounter any issues with scalability.