ScyllaDB Enterprise

What do you like best about the product?

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.

What do you dislike about the product?

It’s self-managed and requires a fairly deep level of technical knowledge to operate effectively.

What problems is the product solving and how is that benefiting you?

ScyllaDB solves the performance bottlenecks common in other NoSQL databases.
While many systems struggle with high latency and slow reads under heavy load, ScyllaDB delivers extremely fast and consistent read performance, even at large scale.
It fully utilizes all CPU cores and scales horizontally without losing speed, eliminating slowdowns and bottlenecks during peak traffic.
In practice, this means near real-time responses and a much more efficient infrastructure.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

I use ScyllaDB as a cost-effective NoSQL database with performance comparable to DynamoDB. It optimizes CPU usage with shard per core, supports SQL-like syntax, and aids in appending message data efficiently.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

I use ScyllaDB to manage stateful information quickly for my real-time app, solving speed and scale issues, allowing me to focus on features rather than performance tuning.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

I use ScyllaDB to improve user authentication with faster read and write speeds than Cassandra, suitable for large user bases. It offers a Cassandra-compatible, shard-per-core architecture for high performance, though it struggles on small VMs.

What do you like best about the product?

I appreciate ScyllaDB for its high performance and low latency in handling NoSQL workloads, making it exceptionally useful for real-time applications such as IoT, finance, and technology, particularly when analyzing time-series data. ScyllaDB stands out as a clear replacement for Apache Cassandra, offering support for the DynamoDB API of AWS, which enhances its applicability and flexibility. I love its thread-per-core architecture, which ensures maximum CPU efficiency by eliminating context switching overhead, resulting in ultra-low latency even under heavy loads. This feature, combined with its predictable performance and automated workload isolation, delivers consistent throughput without stability issues, making ScyllaDB ideal for real-time and high concurrency systems. The database excels in key performance metrics such as scalability and cost efficiency, providing 20x better throughput and more predictable performance under heavy load compared to other NoSQL databases like Cassandra, MongoDB, and DynamoDB. I also value the cloud model ScyllaDB offers, along with its strong support for time series data.

What do you dislike about the product?

I find the documentation depth lacking, which makes it difficult to fully grasp all aspects of the software. The setup process could be more user-friendly, possibly through an agent-based setup. There is inadequate support for complex use cases such as migration and cloud integrations like AWS. Additionally, the tools for data export or import need improvement. I faced hardware challenges initially, which were a significant hurdle during the setup of ScyllaDB.

What problems is the product solving and how is that benefiting you?

I use ScyllaDB for high-performance, low-latency NoSQL workloads, solving scalability and cost efficiency issues. It provides 20x better throughput, predictable performance under heavy load, and is ideal for real-time and high-concurrency systems, clearly outperforming other NoSQL databases.