ScyllaDB Cloud
ScyllaDB, IncExternal reviews
430 reviews
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External reviews are not included in the AWS star rating for the product.
Efficient DB with High Performance, Minor Learning Curve
What do you like best about the product?
I like ScyllaDB's performance-oriented architecture and its compatibility with existing Cassandra tooling, which makes it efficient and scalable. Its focus on efficiency and scalability stands out as key strengths for me. I appreciate how it allows for familiar APIs and workflows to be reused without major changes during evaluations. It's great for evaluating system disparities, ensuring low latency and predictable behavior. Its efficient use of underlying hardware and ease of integration into distributed data architectures needing to grow while maintaining consistent performance makes it valuable.
What do you dislike about the product?
One idea could be, the initial learning curve, especially for people who are new to the distributed database or performance tuning concepts. Some configurations could use some work on that. And establish clearer guidance.
What problems is the product solving and how is that benefiting you?
ScyllaDB addresses high throughput and low latency challenges, maintaining predictable performance at scale. Its performance-oriented architecture and compatibility with existing Cassandra tooling enhance efficiency and scalability, helping us evaluate system disparities and fit into scalable distributed data architectures.
Quick Access and Trusted Backup with ScyllaDB
What do you like best about the product?
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.
What do you dislike about the product?
Nothing too pressing
What problems is the product solving and how is that benefiting you?
ScyllaDB provides easy and quick access to user profiles, offers a centralized storage location, maintains high data accessibility, and offers trusted backup capabilities.
ScyllaDB Delivers Extreme Performance, Low Latency, and Exceptional Scalability
What do you like best about the product?
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.
What do you dislike about the product?
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
What problems is the product solving and how is that benefiting you?
ScyllaDB solves high-volume data, and, unpredictable,,latency bottlenecks by replacing inefficient Java-based systems (like Cassandra or MongoDB) with a C++ shard-per-core architecture. It provides sub-millisecond, consistent performance at petabyte scale, drastically reducing infrastructure,costs, eliminating manual tuning, and ensuring high,availability
Low-Latency Queries, Smooth Overall Experience
What do you like best about the product?
What I like best about ScyllaDB is its high performance and low latency. It’s designed to fully utilize modern hardware, which makes it extremely efficient for handling large-scale workloads while remaining compatible with Cassandra.
What do you dislike about the product?
One downside is that ScyllaDB can be more complex to tune and operate effectively, especially for teams that are new to distributed databases. Understanding data modeling and cluster management is important to get the best performance.
What problems is the product solving and how is that benefiting you?
ScyllaDB solves the problem of handling large-scale data with low latency and high throughput. Its efficient architecture allows systems to process huge volumes of requests without significant performance degradation. This benefits me by providing a reliable and scalable database that can support demanding applications.
Scalable High Performance with Low Latency
What do you like best about the product?
I use ScyllaDB for building high performance backend systems that need large volumes of data with very low latency. I like its performance and latency, as it can process large numbers of read and write operations while keeping the response time fast. I also like its ability to scale easily. Additionally, it's scalable and compatible with Apache Cassandra APIs, which makes integration with tools and systems much easier.
What do you dislike about the product?
One thing that could be improved in ScyllaDB is the complexity of the initial setup. For beginners, cluster configuration and tuning can take some time and requires prior knowledge. More beginner-friendly, simplified tools and setup, clearer responses for common deployment scenarios, and automated config options could help developers start more easily. I think more friendly guides could make the process much easier for new users.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for building high-performance backend systems that handle large data volumes with low latency, efficiently processing many read and write requests even under high traffic, keeping the system fast and reliable as data and users grow.
Highly Scalable and Ready to Grow
What do you like best about the product?
Scalability, quick integration, easy to use guide
What do you dislike about the product?
significant operational complexity, a steep learning curve, high infrastructure cost requirements for optimal performance, and limited suitability for transactional or highly relational data
What problems is the product solving and how is that benefiting you?
Currently I don't use ScyllaDb professionally but looking forward to it.
Lightning-Fast and Reliable, Needs Better Indexing
What do you like best about the product?
I find ScyllaDB to be very fast and robust, which is crucial for my analytics and transactions tasks. I really appreciate the speed it offers, and the faster write capabilities make it stand out for me.
What do you dislike about the product?
Indexing
What problems is the product solving and how is that benefiting you?
ScyllaDB provides me speed and robustness for analytics and transactions.
Scalable and Efficient with Compatibility Plus
What do you like best about the product?
I like ScyllaDB's impressive performance and efficiency, delivering very low latency even under heavy workloads. Its excellent use of available hardware allows us to handle large datasets with fewer nodes, which helps in reducing operational costs. The seamless compatibility with Apache Cassandra is also a big plus, as it makes adoption easier while we still benefit from significant performance improvements and scalability. I value how it allows us to keep our APIs responsive and services stable during traffic spikes.
What do you dislike about the product?
One area that could be improved in ScyllaDB is the operational learning curve. While it performs extremely well once properly configured, tuning and managing clusters can require solid distributed systems knowledge. Some ecosystem tools and documentation are also less mature compared to Apache Cassandra, so troubleshooting or advanced setups may take additional effort.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB as a scalable database for high throughput and low latency needs. It handles large data volumes without bottlenecks, maintains low latency under load, and efficiently manages datasets. Its Cassandra compatibility eases integration while providing predictable performance and better hardware utilization.
Great Engineering, But Needs Improvements Elsewhere
What do you like best about the product?
What I like best about ScyllaDB is its "close-to-the-metal" engineering, which utilizes a shard-per-core architecture to eliminate the CPU contention and "stop-the-world" garbage collection pauses common in Java-based databases like Cassandra.
What do you dislike about the product?
While ScyllaDB is technically superior in performance, it has a smaller ecosystem and less community-contributed documentation compared to the massive Apache Cassandra or MongoDB communities, which can make troubleshooting niche issues more difficult.
What problems is the product solving and how is that benefiting you?
ScyllaDB solves the "Cassandra Migraine" and the "DynamoDB Tax" by eliminating the technical debt of legacy NoSQL architectures, specifically addressing unpredictable tail latency caused by Java's garbage collection and the agonizingly slow scaling of static token rings.
ScyllaDB: Predictable Low Latency and High Throughput at Scale
What do you like best about the product?
ScyllaDB delivers extremely low latency and high throughput at scale, which helps keep performance predictable even under heavy load. Its shard-per-core architecture and efficient I/O scheduling allow it to fully utilize modern hardware without constant tuning, and that can reduce the number of nodes we need. I also appreciate that it’s largely Cassandra-compatible while being much faster, so you get a familiar data model and ecosystem, along with better tail latencies.
What do you dislike about the product?
ScyllaDB still comes with a learning curve, particularly when it comes to data modeling and capacity planning. If you get the model or the underlying infrastructure wrong, performance can degrade quickly. It also assumes you have solid hardware and that you make careful choices around storage and memory, so it’s less forgiving than simpler databases. Because of that, it can feel like overkill for smaller or more generic workloads.
What problems is the product solving and how is that benefiting you?
ScyllaDB addresses our need for consistently low-latency reads and writes on large, write-heavy workloads where traditional relational databases or slower NoSQL options tend to struggle. It allows us to support real-time, high-throughput use cases—such as event ingestion and time-series or key-value access—on fewer nodes. As a result, we can reduce infrastructure costs while still meeting strict SLAs.
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