ScyllaDB Cloud
ScyllaDB, IncExternal reviews
426 reviews
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Excellent NoSQL Solution with High Availability and Strong Performance
What do you like best about the product?
Excellent no sql solution with High availability, user personalization and performance driven DB solutions out there
What do you dislike about the product?
Little complex to start with, and takes a while to get used to it
What problems is the product solving and how is that benefiting you?
DaaS, cost effectiveness and best deployment with higher throughput
Efficient Data Storage with ScyllaDB's Sharding and Performance
What do you like best about the product?
I appreciate ScyllaDB's sharding and native change data capture, which are pretty significant features that stand out for me. The performance is really a big plus, making it faster for me to get to market. These aspects are crucial, especially when dealing with NoSQL data storage.
What do you dislike about the product?
I dislike the Docker distribution.
What problems is the product solving and how is that benefiting you?
ScyllaDB helps me store NoSQL data efficiently, with features like sharding and native change data capture enhancing performance and speeding up our go-to-market efforts.
Efficient Scaling with Top-Class Compatibility
What do you like best about the product?
I use ScyllaDB for efficient storage. I appreciate its tail latency guarantees and the fact that it scales well beyond my needs, so I don't need to worry about migrating anywhere. I like its compatibility with CQL and the custom extensions that are performance-oriented, such as bypassing the cache for certain queries. I find their Rust driver to be top class for both ScyllaDB and Cassandra, and it's important because latency-sensitive systems are often built in Rust. I also enjoy that the whole ecosystem of tools that works with Cassandra works with ScyllaDB too. The initial setup was easy to follow from the docs.
What do you dislike about the product?
I sometimes wish for more SQL compatibility, like being able to send a complex query that joins multiple tables.
What problems is the product solving and how is that benefiting you?
I trust ScyllaDB's tail latency guarantees and its scalability beyond my needs, so I don't need to worry about migrating. It provides efficient storage.
High-Performance, Needs Better Documentation
What do you like best about the product?
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.
What do you dislike about the product?
I find the documentation and tutorials lacking. They could really use more detailed examples for vector search.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for handling large volumes of concurrent reads. The vector search means I don't need a separate vector database, which I find valuable.
High Throughput That Delivers
What do you like best about the product?
High throughput and reduced latency withh redundancy
What do you dislike about the product?
Nothing in particular but it has steep learning curve
What problems is the product solving and how is that benefiting you?
Better Performance: Faster, more responsive applications.
Cost Savings: Lower infrastructure spend due to higher efficiency.
Simplified Operations: Less time spent on database tuning and maintenance.
Future-Proofing: Easily scales as data volume grows.
Cost Savings: Lower infrastructure spend due to higher efficiency.
Simplified Operations: Less time spent on database tuning and maintenance.
Future-Proofing: Easily scales as data volume grows.
Easy to Use with Low Latency
What do you like best about the product?
I find ScyllaDB easy to use, which was great for my project. I also really like its low latency and the initial setup had good ease.
What do you dislike about the product?
It was new for me, so learning curve
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for storing data in my URL shortening project. It's easy to use and offers low latency.
High-Performance with Learning Curve Challenges
What do you like best about the product?
I use ScyllaDB for handling large-scale data in high-performance applications. I like its high performance and low latency when handling large amounts of data. It is designed to efficiently use modern hardware, making data processing very fast. Its compatibility with Apache Cassandra is great since it makes it easier for developers to migrate existing systems. I find the shard-per-core architecture, which efficiently utilizes modern multi-core CPUs, to improve performance and resource usage. Its compatibility with Apache Cassandra supports the same CQL (Cassandra Query Language), making migration easier without needing major code changes. The ability to deliver very low latency and high throughput is ideal for real-time applications that process large volumes of data.
What do you dislike about the product?
One area that could be improved in ScyllaDB is its learning curve for beginners, especially when setting up and managing clusters. The configuration and performance tuning can be complex for new users. Additionally, better documentation and simpler setup tools would make it easier for developers to get started quickly.
What problems is the product solving and how is that benefiting you?
ScyllaDB handles large-scale data efficiently, providing high speed and low latency. It supports real-time applications with key-value data storage and retrieval, making scalable, fast, and reliable backend systems possible.
Predictable Performance, Low Latency at Scale with ScyllaDB
What do you like best about the product?
I appreciate ScyllaDB for its predictable low latency at scale, with P99 latency staying in the single-digit millisecond range even under heavy load. I like that we can use fewer nodes while achieving the same or better throughput, which makes our cluster much smaller. The ability to store both our key-value and vector workloads in one database is a big plus, eliminating the need for a separate vector database for RAG and semantic caching. The CQL compatibility is beneficial as it uses the same query language and driver model as Cassandra, easing both migration and hiring. The Shard-per-core-design is a standout feature—it scales performance predictably with core additions, reducing surprises under load and minimizing the need for constant tuning to avoid hotspots or mysterious latency spikes.
What do you dislike about the product?
Vector search is only on ScyllaDB Cloud right now, and we'd like to see it in open-source/self-managed for on-prem and air-gapped use. Data modeling is strict: partition key design and row/partition size really matter, and it's easy to paint yourself into a corner if you don't plan upfront. There's also a learning curve around compaction strategies, consistency levels, and limits (e.g., tables per keyspaces, partition size) that we had to absorb before we felt confident.
What problems is the product solving and how is that benefiting you?
ScyllaDB provides high write throughput and low latency at scale, allowing us to use fewer nodes with predictable performance. It unifies key-value and vector data needs, eliminating the need for separate databases, and facilitates scalable capacity planning with its shard-per-core design.
High performance and scalable NoSQL database.
What do you like best about the product?
I loved the performance and scalability while ingesting or retrieving high amount of data.
What do you dislike about the product?
I am still learning about it so nothing so serious issues I found till now though I would love to see more documentations around configurations and operational management.
What problems is the product solving and how is that benefiting you?
Our data is evolving, scylladb solving performance and scalability issues. it has drastically improved the query latency when we deal with nested/raw data. it best fit for our near real-time data processing framework.
Real-Time Data Processing at Lightning Speed
What do you like best about the product?
I like ScyllaDB for its speed and adaptability. It helps us generate real-time reports and identify and resolve data-related issues with no outage. I appreciate how ScyllaDB can handle data from multiple sources like mobile devices and various streams, making real-time processing really fast and suitable for all kinds of data. I also like its ability to adopt various data sources.
What do you dislike about the product?
AI agent integration
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for real-time data processing, helping to generate reports and resolve issues during outages efficiently.
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