ScyllaDB Reviews

We use the platform to manage advertising-related data, such as tracking ad views and demographic information.

The product's most valuable features are efficiency and reliability. Compared to similar tools, it consumes fewer computing resources and requires minimal maintenance, ensuring smooth operations.

I have been using ScyllaDB for approximately three years. 

We've had occasional performance challenges that required resource adjustments or optimizations in our interaction with the platform. However, the support team has responded and promptly resolved these issues.

I rate the stability a nine. 

The product is highly scalable.

The technical support team has been excellent. They are responsive and knowledgeable, providing timely assistance.

The initial setup has been straightforward in our experience. The deployment team handles the setup efficiently, typically completing it within a day with minimal involvement required from our side.

The product's efficiency has allowed us to optimize resource usage effectively. Its reliability reduces operational overhead, enabling us to focus resources on other critical tasks.

It is user-friendly for those familiar with databases. A basic understanding of database management is necessary for effective use and deployment.

I rate it a ten. 

We dump a lot of our data, such as every entry created with respect to when a user rides a scooter, every record gets updated to ScyllaDB. It is used as a single source of truth and it manages massive data. 

We support various business use cases, including mobility, where data about driver allocations get updated. We currently have twenty clusters and more than one hundred nodes.

The performance and scalability are good, and we hardly see any major issues with ScyllaDB. Updates are reliable and help the organization handle large datasets effectively.

To be honest, not really. We were sold on the pitch, offering better compaction and ROI, but we did not experience these benefits.

From a sales pitch standpoint, it needs to deliver on promises of better ROI and compaction. Additionally, ticketing and support systems could be improved due to the time it takes to get answers. There's also an issue with compatibility when attempting to switch back from the enterprise to the community version.

I would say probably five years by now.

The performance and stability are fine. We hardly see any major issues, and from a reliability standpoint, it's all good.

Due to organic growth, we end up upgrading the cluster and adding more nodes. In terms of reliability, it's all good, but specific benefits from scalability were not highlighted.

The technical support and customer service are around a five or six out of ten. Improvements can be made in ticketing and response times.

Neutral

We used to work with Cassandra. During our initial phases, we found ScyllaDB promising due to its implementation language and maintenance, which led us to adopt it over Cassandra.

Migrating to the enterprise version from the community version is straightforward and supported, but moving back to the community version is complex due to compatibility issues.

To be frank, not really. The open-source version sufficed our use case without requiring the costly enterprise version.

The enterprise version comes with a cost of about $300,000 per year, however, we did not experience the promised compaction benefits.

We evaluated Cassandra during initial proof of concepts.

I would suggest using ScyllaDB wisely and adhering to best practices, such as regular cleanup since many engineers tend to expand clusters instead of cleaning up data. I would rate ScyllaDB as eight out of ten.

Our company currently uses Scylla for our products since we are in the process of migration from Postgres.

Our company is reimplementing the user data pipeline and needs faster results. We found Scylla to be preferable for our use case from the alternatives we evaluated.

User-defined type in Scylla allows for data to be consistent. The performance aspects of Scylla are good, as always. The product's flexibility allows us to use Cassandra SDK with it while also being able to migrate from DynamoDB to it. A good point about Scylla is that it can be used extensively.

It has just been a month or so for me with Scylla. The documentation of Scylla is an area with shortcomings and needs to be improved. Improvement of documentation is needed considering that I work with Java. We currently use a data stack model, which is actually for Cassandra. There is no different dependency for Scylla, so it's adding a wrapper on the SDK that Cassandra supports, and we end up just using it.

I think it's good as it is. I don't have any input on what needs to be added in Scylla.

I have experience with Scylla for around two months. Currently, I am learning more about Scylla. I am using the solution's latest version. My company is a system integrator. We have different verticals, and one of it is that we are moving into is integrating, which is running our product as a binary in our enterprise solution and on clients' machines.

Stability-wise, I rate the solution a nine out of ten.

Currently, we are involved with Scylla's prototype version. For the project that I am working on, Scylla is not being used, and it is not just the case with my project alone but also with a huge number of projects because they are moving to cloud-agnostic architecture. We are moving all the DynamoDB databases to Scylla. Within a year or so, all of our DynamoDB databases will be replaced.

To be able to rate Scylla's scalability, we would need time since we are using its prototype.

Previously, I have used MongoDB for other projects.

We actually are not switching from MongoDB. We have a couple of alternatives for what we are building, and we wanted to know about SQL because we may have to change our schema quite a bit because we used to have a lot of metadata, and that's why the traditional RDBMS will have to split the columns instead of rows, making it very intense.

Scylla is a cloud-based solution. We are moving to a cloud-agnostic architecture, so we would have different instances based on our enterprise solution or the client.

Whether to use a private or public cloud depends on the requirements of our clients.

In my local environment, the installation part was quite easy because it's a Docker installation. I don't know about the remote installations with Kubernetes because that is managed by the cloud tech team.

I have been working on the solution for around a month, so it is mostly the people involved in the cloud tech department who look at things like the maintenance of the solution, an area in which I have no idea.

A weird error can pop up owing to the flaws in the documentation, because of which I am using an ORM tool to interact with the database. If required in a particular use case, I return a list of objects, or a list of a user data type, when it throws an error indicating that I should reimplement the codec. When I changed the codec to set, it started working fine. The aforementioned issue was not figurable even in Stack Overflow.

Overall, I rate the solution an eight out of ten.

Scylla is used as a cache. Once the data is ingested into the product during the initial load, a version of it is stored in Scylla DB, and this is then used by the other transformation services to query and make updates during ongoing loads. That is, it is being queried by other services to make the updates whenever deletes occur.

It is lightweight, and it requires less infrastructure.

Data export, along with how we can purchase the data periodically, needs to be improved so that the storage is within control. Then, we could optimize it even better.

This is not a very old product, and it's seven or eight months old.

We would like to leverage it on the public cloud, but due to some limitations at the moment, it's on the cloud but using IAS. We have virtual machines, and there, we have created the cluster.

It's pretty much stable. We have been in production for six months now, and I haven't seen it go down. We have had a few instances where one or two of the nodes have gone down, but the cluster has been stable.

Scalability in performance is good. We can add more nodes and have more scalability. We have about 200 people using this solution.

Support and the availability of support need improvement. I would give them a six out of ten.

Neutral

The architecture team did some tests and performance benchmarking, and they found out that in comparison to that for other tools almost one eighth or one tenth of the infrastructure was required for Scylla and that the performance was the same.

This is built on using C++, and it's very lightweight, whereas the others were using too much infrastructure. These are some of the reasons why Scylla was chosen.

I believe that there is a yearly licensing cost and that it's expensive.

The architecture team evaluated MongoDB and Cassandra.

Overall, I would give Scylla a seven out of ten for our use case.