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.
The best features of ScyllaDB are how it synchronizes data and its failover system. There's a unique formula to decide the number of nodes you need and the minimum required, which I find helpful. It also offers encryption and supports APIs, making it great for distributed systems
and scaling databases across different regions. While it's easy to use, having prior experience helps configure it properly. There are many configurations; if you don't understand them, you might mess up the design. So, understanding your system's needs, like whether it requires more read or write operations, is crucial for setting up the correct configuration.
It seems we have better options available. So probably don't go for ScyllaDB. The reason is, first, it's very high. It's not as straightforward as, like, Postgres or ClickHouse to set up. It requires a complex setup.
We faced several challenges while integrating ScyllaDB into our AWS environment. One common issue was that a security port wasn’t opened on one node, preventingdata synchronization across clusters. We noticed the data wasn’t syncing correctly when we saw different record counts in other regions. After investigating, we found that the port was closed in one AWS region. Once we opened the port, the data synchronization across all nodes resumed as expected.
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.
