ScyllaDB Cloud
ScyllaDB, IncExternal reviews
400 reviews
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External reviews are not included in the AWS star rating for the product.
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.
Cost-Efficient with Standout Performance
What do you like best about the product?
I like using ScyllaDB because of its standout performance and low maintenance requirements. It helps me handle a large number of events and logs efficiently without breaking the bank, providing low latency and high throughput which are very valuable.
What do you dislike about the product?
I find the documentation and out of box integration with ScyllaDB lacking. Troubleshooting can be hard, and the initial setup was difficult because it was new to us.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB to handle a large number of events and logs without breaking the bank, enabling low latency and high throughput, and its performance is standout while being low maintenance, which reduces costs.
Fast and Cost-Efficient for Data Streams
What do you like best about the product?
I use ScyllaDB for educational purposes and I'm impressed with its scalability and cost efficiency. The self-serviced infrastructure is a bonus, and I find the 90% consumption utilization feature very cost-efficient. It's also impressively fast on large data stream real-time analysis. The initial setup was quite easy due to the many available resources.
What do you dislike about the product?
I am generally happy with it. Maybe the time it takes to start the cluster could be faster.
What problems is the product solving and how is that benefiting you?
ScyllaDB is scalable, cost-efficient, with self-service infrastructure. The 90% consumption utilization is economical, and it's very fast for real-time analysis of large data streams. It helps me understand data ingestion technologies better.
Implementation-Friendly
What do you like best about the product?
Adopting ScyllaDB into our existing setup without any hassle has been the most welcome part, as it feels very implementation-friendly.
What do you dislike about the product?
The time it takes to integrate with a production environment in a hybrid cloud setup is a bit of a concern.
What problems is the product solving and how is that benefiting you?
High performance with the expected scalability in a multicloud environment is very beneficial.
Effortless Setup, Maximized CPU Utilization
What do you like best about the product?
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.
What do you dislike about the product?
I don't like that the open source is not released after version 5.2.
What problems is the product solving and how is that benefiting you?
ScyllaDB allows our database to fully utilize CPU resources, offering improvements with rolling upgrades, node replacement, and Grafana integration that makes it easy to understand live operations.
High Performance, Low Latency Database Solution
What do you like best about the product?
I like ScyllaDB for its high performance and low latency, even when handling large-scale workloads. The compatibility with Cassandra makes migration and integration easier for us. I also appreciate its efficient resource utilization, allowing us to get better performance with the same hardware, and its strong scalability.
What do you dislike about the product?
One area that could be improved is the learning curve for new users as configuring and tuning can be a bit complex at first.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB to store large volumes of data. It handles high-throughput workloads with low latency and is highly compatible with Cassandra, easing integration. It enhances performance with better resource utilization and provides strong scalability.
Low Latency and Seamless Data Integration
What do you like best about the product?
I use ScyllaDB as a database store for internal management services like ticketing management. One thing I like most about ScyllaDB is the low latency. I had tried Redis; it was low but expensive, so I had to switch. Then I saw the Last Monster Summit and decided to try ScyllaDB, and till now, I have no regrets. Users see updates on the leaderboard instantly instead of waiting 400ms with the database. This low latency was the main driver for switching from Postgres and Redis to ScyllaDB. Initially, the setup was good.
What do you dislike about the product?
One thing I felt that could be improved is a bit on documentation and some examples for already setup systems would be appreciated.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for high data throughput, preventing data loss. It offers low latency, making leaderboards update instantly instead of waiting for 400ms.
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