ScyllaDB are its extreme performance, low latency, and exceptional scalability. It is widely considered a superior, high-performance alternative to Apache Cassandra, often allowing users to handle larger workloads with fewer nodes. Review collected by and hosted on G2.com.

the main drawbacks of ScyllaDB revolve around its steep learning curve, operational complexity, and the specialized, high-resource hardware required to achieve its promised performance Review collected by and hosted on G2.com.

I like the rolling upgrades, node replacement, and Grafana integrations with the Scylla exporter, as they make it easy to understand the live workings of the system. I also appreciate that ScyllaDB allows the database to fully utilize the CPU, solving CPU core shared issues. The initial setup of ScyllaDB was so easy. Review collected by and hosted on G2.com.

I don't like that the open source is not released after version 5.2. Review collected by and hosted on G2.com.

It's similar to MongoDB but have more features like accessing data fastly through query, etc. Doing more research to find the fetures. Review collected by and hosted on G2.com.

Not found any yet. But if I see any then will notify you. Review collected by and hosted on G2.com.

I use ScyllaDB as a NoSQL database for appending message data before transitioning it to downstream services, where its efficiency stands out significantly. ScyllaDB is cheaper than DynamoDB, yet it offers comparable or sometimes even superior performance, which is highly beneficial for cost-effective scalability. I appreciate the SQL-like syntax that ScyllaDB provides, which enhances the usability by making it easier to query and manage data. The shard-per-core architecture is particularly impressive because it allows us to maximize CPU utilization, squeezing out extraordinary levels of performance, which is critical for our intensive processing needs. Additionally, the support team at ScyllaDB has been incredibly active and helpful in troubleshooting, making the transition smooth and instilling confidence in the adoption of their system. Review collected by and hosted on G2.com.

I find the lack of support for lightweight transactions (LWT) across nodes or partitions challenging. This limitation makes it difficult to handle transactions in a manner similar to PostgreSQL, where transactions can touch multiple tables in the database. Additionally, I would appreciate built-in support for retries, which is currently lacking and impacts the ease of handling transactions effectively. Review collected by and hosted on G2.com.

I use ScyllaDB as the high-performance backend database for my real-time voice chat application, and I am thoroughly impressed by its ability to efficiently manage stateful information with remarkable speed and reliability. ScyllaDB effectively handles a huge volume of reads and writes effortlessly, removing the constant worry of the database becoming a bottleneck. Its reliability allows me to focus on building my application's features instead of constantly tweaking performance. Additionally, its setup was surprisingly straightforward due to Docker, as I simply pulled the official ScyllaDB image and added it to my docker-compose.yml file, which significantly reduced the complexity of installation. Its seamless integration with my Go application via the gocql driver, along with its operation inside Docker as part of my main development stack, underscores its adaptability and ease of use in diverse development environments. Review collected by and hosted on G2.com.

I find the learning curve for ScyllaDB quite steep, especially for newcomers to distributed NoSQL databases. Transitioning from a SQL background requires a significant shift in data modeling approach, and understanding concepts like consistency levels, replication, and query patterns isn't straightforward. This complexity can be daunting and requires a dedicated effort to grasp fully. Review collected by and hosted on G2.com.

ScyllaDB is fast, highly scalable, and efficiently uses all CPU cores. It handles millions of operations per second with consistent performance, scales easily by adding nodes, and has excellent, practical documentation. Review collected by and hosted on G2.com.

It’s self-managed and requires a fairly deep level of technical knowledge to operate effectively. Review collected by and hosted on G2.com.

I really appreciate ScyllaDB's scalability, which is the number one thing I like about it. It allows me to combine multiple events and orchestrate between them seamlessly. ScyllaDB handles low latency well, letting me scale up easily, especially with large training datasets involving 100,000 plus people. It also manages real-time workloads efficiently, helping me coordinate multiple events smoothly. Review collected by and hosted on G2.com.

NA Review collected by and hosted on G2.com.

I like the vector search feature in ScyllaDB because it means I do not need a separate vector database. The initial setup was quite easy for me because it's not so different from other tools, and there are a lot of tutorials available on the internet. Review collected by and hosted on G2.com.

I find the documentation and tutorials lacking. They could really use more detailed examples for vector search. Review collected by and hosted on G2.com.

I like ScyllaDB because it offers quick and easy availability, which makes accessing user accounts and their information smooth. I also appreciate its trusted backup capabilities, ensuring our data is secure and accessible. Additionally, I find ScyllaDB's ability to keep a high level of data accessible in multiple ways very beneficial for all our internal users, allowing access on the go. Review collected by and hosted on G2.com.

Nothing too pressing Review collected by and hosted on G2.com.

I appreciate ScyllaDB's significant improvement in read and write speeds compared to Cassandra, which is crucial for our project with a large user base of around 80 million. I value the Cassandra compatibility of ScyllaDB, allowing for an easy lift and shift process. Additionally, the shard-per-core architecture is excellent for performance enhancement, particularly in high user base environments. Even though it took some time to understand its architecture initially, the potential for higher performance outweighs the learning curve. Review collected by and hosted on G2.com.

ScyllaDB doesn't perform well on small VMs. The initial setup took some time to understand its architecture and internal mechanisms. A relaxed CPU pinning mode could improve stability on over-subscribed cloud hosts. Review collected by and hosted on G2.com.