ScyllaDB Reviews

We use ScyllaDB, a NoSQL database, as a distributed system to store customer data. My last project was in telecommunications, where we stored caller information like phone numbers, names, and scam tags for a scam call protection service. We handled insert, update, and other operations since the back-end AI system needed daily data inputs. We ran scripts to add the data to ScyllaDB across two AWS regions: US East and US West. One Scylla node handled requests, synchronizing data with its peer nodes. During the POC phase, we testedperformance, read/write operations, and latency and chose the right consistency levels for ourneeds. After that, we moved to production.

We are customers, not partners, and we’ve used ScyllaDB to implement an application in our company.

ScyllaDB is a very seamless product within C++ or something. So, it's faster and all that stuff. Even if it is all good, there is more need for marketing on their website than on the original thing. 

Now, if you are a big company, ScyllaDB is a good, robust product. It's a terabyte/petabyte kind of product. But your cost would be one-third or even less with ClickHouse, and it would be smoother and lighter.

ScyllaDB is very fast, and I can use it for so many things. But what happened is we pushed a lot of data, and even though it was fast, things started getting weird here and there. 

At one point, we could understand why accepting this when you restart something or fix something and it starts working. You feel very smart, like, " Oh yeah, we did it right." But then again, these are the problems we shouldn't be having in the first place. 

But it is fast and very distributed. So, let's say you're Google, and you need your server in 500 places, and they all should talk with each other in close proximity. And you deploy ScyllaDB and have a dedicated DevOps version full-time. It's going to work. So, those things are there in ScyllaDB. But, again, it requires a full-time job.

We used ScyllaDB as an alternative to MongoDB. Our company's MongoDB servers experienced malicious attacks, so we migrated to ScyllaDB. 

We read from MongoDB and wrote everything to ScyllaDB because it's considered safer than MongoDB.

There are two that I like most. Firstly, if I update something, it's most likely to finish within milliseconds. Anything can be updated without writing too much code. Secondly, I like CDC.

We have a business model that requires heavy reads for several applications all in one place. So we decided to use ScyllaDB because of the workload, to have multiple reads and writes at the same time.

I like how fast it is to query data from the ScyllaDB node! Because it can actually enable you to query any data from any node as fast as possible. And the ability to save the same copies of data across the cluster, depending on your setup as well. It's really fast.

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.

For security reasons, we collect millions of signals and put them into the S3 bucket. Once we run Spark job on the raw data, we take all that data and send it to ScyllaDB.

ScyllaDB allows fine-tuning of the table structure. Speed is probably the most critical factor because we perform a lot of heavy data ingestion. One of its core features is its ability to handle high volumes and maintain speed when accessing data. Additionally, high availability and partitioning are built-in features of ScyllaDB.

We use the solution to present information for a very big system. The dashboard requires real-time information.

ScyllaDB provides access to information directly using SQL language.

We use it as a non-relational database. We use it to store two things:

1.  To store audit log data and 
2. blob data, including images with different sizes, like 200kb.

We use it as an image database as well, such as user profile pictures and product catalog promotional pictures.

ScyllaDB is a rewrite of Cassandra in C++ and uses a special library called Seastar, which was developed by ScyllaDB. 

Seastar is optimized for I/O operations, which makes it very good compared to Cassandra. Like it's ten times better in terms of performance.

The documentation is good. It integrates easily with our existing data infrastructure.