For our log data aggregation and analysis platform, ScyllaDB offers unparalleled performance and scalability. Real-time processing of millions of log events per second has relied heavily on its capacity to manage high-throughput writes with incredibly low latency. We also value the low operational overhead—compared to other NoSQL databases, ScyllaDB uses less infrastructure because of its auto-tuning features and effective hardware utilization. In particular, the native support for time-based TTLs is useful for automatically controlling log retention. It just operates on a larger scale. Review collected by and hosted on G2.com.

ScyllaDB has a learning curve for teams used to Apache Cassandra or more traditional relational databases even if it boasts better performance. For some complex tuning parameters and architectural ideas, such log analytics, optimal performance for particular workloads depends on a better knowledge. Moreover, even if the documentation is usually good, some edge cases—especially those related to large-scale cluster management and repair activities—would benefit from more practical examples. The community and support network, however, are flexible which helps to close the distance. Review collected by and hosted on G2.com.

Indexing makes searching data very fast and easy

Handles large metric data smoothly with low latency

Works well for real-time analytics and monitoring

Scales easily as more metrics are added Review collected by and hosted on G2.com.

Nothing to dislike here but It takes time for new users to understand indexing setup. Review collected by and hosted on G2.com.

ScyllaDBs handling of indexing and search is very efficient. Even when the data grows, queries still run smoothly. It uses hardware well that we do not need any setup work, the speed can be quite high as the software does not put extra burden on. Review collected by and hosted on G2.com.

Cluster scaling works well, but setting it up the first time can be a bit tricky.Monitoring tools could be easier to use for new users Review collected by and hosted on G2.com.

ScyllaDB gives very low latency even when our product has a lot of traffic. Scylladb's sharding system is amazing, also helps to spread the data across nodes, so no single node gets overloaded. we are able to handle millions of requests without any performance issues. Review collected by and hosted on G2.com.

There is nothing major to dislike about scylladb. Only the community support is less as compared to other alternatives. Review collected by and hosted on G2.com.

As a software consultant, I find ScyllaDB to be a high-performance, distributed NoSQL database that excels in scalability and low-latency operations. Its compatibility with Cassandra makes migration and integration straightforward, and many users report that it is easier to administer than Cassandra, with less tuning required . While initial setup can be more complex than some relational databases, ScyllaDB’s architecture allows for efficient use of modern hardware and offers robust features such as built-in caching, encryption, and monitoring tools . Integration with existing systems is generally smooth, and the database is frequently used in production by major enterprises for data-intensive workloads . Customer support is strong, especially for enterprise clients, and the active community and regular updates ensure ongoing improvements. However, documentation and some advanced features could be more comprehensive, and secondary indexes may impact write performance . Overall, ScyllaDB is a powerful choice for organizations needing speed, scalability, and reliable support. Review collected by and hosted on G2.com.

While ScyllaDB offers impressive performance and scalability, there are several areas where it falls short for my use cases. The initial setup and configuration can be quite complex compared to more traditional databases like PostgreSQL, often requiring careful resource planning and tuning. Debugging and analyzing issues can also be challenging due to the system’s complexity, and maintenance efforts tend to be higher than expected. I’ve found the documentation lacking in some areas, which makes troubleshooting and advanced configuration more difficult. Additionally, ScyllaDB’s support for transactions is limited, and features like secondary indexes and multi-key transactions are either not fully supported or have notable limitations. The community around ScyllaDB is relatively small, which means finding help or shared experiences outside of official channels can be difficult. These factors combined can make ScyllaDB a less approachable choice for teams without deep NoSQL expertise or those looking for a more mature ecosystem. Review collected by and hosted on G2.com.

I used to use Postgres as my go-to database. When I started using Scylla, its SQL-like syntax made it super easy for me to get used to it. Not only is it easier to get used to, but it's also lightning fast. Plus, Cassandra compatibility! I don't think I can ever go back to using Postgres again after experiencing this (unless it's part of the project requirement). Now, Scylla is my go-to database. Review collected by and hosted on G2.com.

I'd be nitpicking here, but there are times when I just want to fetch something without using all partition keys or to update a field that happens to be a clustering key. Not as part of my project or test (that would be silly), but just for some random reason. Of course, that doesn't work the way it does with SQL. That's something I miss. But I really can't blame Scylla for this, I could have used any NoSQL database and the same would have been true. Review collected by and hosted on G2.com.

It’s really fast and handles a lot of data without slowing down. I like that it’s easy to scale and doesn’t need as much tuning as Cassandra. The global secondary indexes and other modern features are also very helpful. I like the sessions as well, very interactive + gives hands on experience. Customer support also gives timely response. Additionally, it was easy to integrate, my company Samespace uses it, overall its very handy and is frequently used Review collected by and hosted on G2.com.

Some features are still a bit limited, and using secondary indexes can slow down writes. Also, the setup and docs can be a little hard to follow if you're new, but university was a great way to get myself started Review collected by and hosted on G2.com.

ScyllaDB is very fast and handles thousands of data records at one time without any delay. The latency is very low, and the throughput is excellent. It helps keep the ML data pipeline stable and quick. Review collected by and hosted on G2.com.

Sometimes it can be hard to monitor and manage cluster performance when the data size keeps growing. A simpler built-in dashboard for tracking and tuning would be helpful. Review collected by and hosted on G2.com.

ScyllaDB is very fast and has low latency. It handles our healthcare data without delay. The system stays smooth even when data is big. It is easy to read and write data quickly. Review collected by and hosted on G2.com.

Community support is lagging as compared to other popular similar databases. It's hard for a new developer to get hands on it. Review collected by and hosted on G2.com.

The best thing about ScyllaDB is it's internal indexing strategy that helps in great performance while retrieving millions of logs data.The inbuilt metrics monitoring software (grafana) is also a really amazing and we does not need to separately setup the monitoring and metrics dashboard. It's well suited for logs, real-time, and time-series data analytics. Review collected by and hosted on G2.com.

Sometimes the documentation requires more efforts to understand it's internals. I also felt that learning curve in scylladb is different as compared to other databases like Cassandra. But once, we get enough practice, it's just super easy. Review collected by and hosted on G2.com.