ScyllaDB Enterprise
ScyllaDB, IncExternal reviews
326 reviews
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Best Database for Real Time Gaming Systems
What do you like best about the product?
- Handles huge amounts of data with no slowdown
- Very low delay, best for real-time apps like gaming
- Easy to add new servers and balance data
- Runs on any cloud
- Very low delay, best for real-time apps like gaming
- Easy to add new servers and balance data
- Runs on any cloud
What do you dislike about the product?
- Some features like graph queries or search are missing
- Not always easy for beginners to learn
- Not always easy for beginners to learn
What problems is the product solving and how is that benefiting you?
- We use it to track live user data in games (Real time gaming)
- Can handle millions of actions from players at the same time
- Data is safe and always available, even if a server fails
- Makes our platform fast and smooth for users
- Can handle millions of actions from players at the same time
- Data is safe and always available, even if a server fails
- Makes our platform fast and smooth for users
Best NoSQL Database for Performance and Latency
What do you like best about the product?
ScyllaDB is very fast and can handle a lot of with great efficiency. It works well for real-time use, heavy writes, and large-scale systems like IoT or analytics. Adding new nodes is quick and easy, and the data gets balanced automatically. It also works with Cassandra, so moving to it is simple. I also like that it runs on any cloud and supports containers.
What do you dislike about the product?
Some features, like graph queries or advanced search, are missing compared to other databases. It can also take time to learn and set up, and the docs could use more real-world examples. Like most NoSQL systems, you have to deal with things like eventual consistency and fewer options for joins or transactions.
What problems is the product solving and how is that benefiting you?
We wanted a database that can scale easily and stay fast even with very large data. ScyllaDB lets us store and process data across different regions and keep it available all the time. It helps with real-time analytics, security data, and other workloads that need low latency.
Fast and cost-friendly database for indexing and search
What do you like best about the product?
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.
What do you dislike about the product?
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
What problems is the product solving and how is that benefiting you?
We use ScyllaDB for fast lookups and indexing. It makes it easier to scale as our data gets bigger. We don’t need to spend extra on hardware, so it helps us cut costs and stay efficient.
Super fast and reliable NoSQL Database for recommendation systems
What do you like best about the product?
ScyllaDB is very fast. We store a lot of user data like clicks, views, and preferences, and it handles everything smoothly. It’s easy to scale when we need more performance because of it's auto-scaling mechanism which is really very efficient. Due to it's lockless, shared-nothing architecture it's able to handle concurrent reads and writes very efficiently.
What do you dislike about the product?
You’ll need some time to understand how to design the data model the right way, otherwise everything is good.
What problems is the product solving and how is that benefiting you?
Our user recommendation system is powered by ScyllaDB. It enables us to present the appropriate goods and information to the appropriate audience at the appropriate moment. Without slowing down, it manages thousands of user actions daily. Our users now receive better recommendations, and our system is more efficient and reliable than before.
Best Database At Scale : ScyllaDB
What do you like best about the product?
It supports CQL (Cassandra Query Language), so migrating or integrating with Cassandra-based systems is very easy. Automatic Sharding and Load balancing reduces our operational overhead and it makes the node management very easy. In-built Grafana monitoring tool is really awesome, we do not need to set them up separately.
What do you dislike about the product?
ScyllaDB Cloud does not provide a way to visually browse databases, tables, or data rows. While it’s growing, there are fewer integrations or community tools.
What problems is the product solving and how is that benefiting you?
We use ScyllaDB for our internal data indexing and machine learning pipelines, which need to be fast and able to grow. ScyllaDB takes care of data distribution on its own and makes it easier for us to manage our database nodes, which saves us time on maintenance. Since we use ScyllaDB Cloud, scaling and upkeep are taken care of for us, letting our team stay focused on analytics and building better models instead of worrying about infrastructure.
A Consultant’s Perspective on Usability, Features, and Integration
What do you like best about the product?
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.
What do you dislike about the product?
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.
What problems is the product solving and how is that benefiting you?
At the moment we are looking for options to be our Database for a new APP that we will launch this year.
ScyllaDB Experience Review: A Developer’s Perspective
What do you like best about the product?
1. Blazing Fast Performance
Latency: Ultra-low latency even at high throughput.
Throughput: Handles millions of operations per second per node.
Example: Users report up to 10x better performance than Cassandra in the same hardware.
Latency: Ultra-low latency even at high throughput.
Throughput: Handles millions of operations per second per node.
Example: Users report up to 10x better performance than Cassandra in the same hardware.
What do you dislike about the product?
While it uses CQL, it’s still a NoSQL DB.
Not ideal for relational joins, ad-hoc analytics, or OLAP workloads.
2. Schema Evolution is Painful
Altering schemas, adding indexes or materialized views can impact performance or require careful planning.
3. Learning Curve
New developers may struggle with:
Data modeling that fits Scylla's partition/key-based logic.
Not ideal for relational joins, ad-hoc analytics, or OLAP workloads.
2. Schema Evolution is Painful
Altering schemas, adding indexes or materialized views can impact performance or require careful planning.
3. Learning Curve
New developers may struggle with:
Data modeling that fits Scylla's partition/key-based logic.
What problems is the product solving and how is that benefiting you?
Time-Series Data Storage
Use Case: IoT sensors, monitoring systems, geolocation tracking
Why ScyllaDB:
Efficient partitioning and TTL support
Optimal for append-only, timestamped data
Compact storage with compression
Use Case: IoT sensors, monitoring systems, geolocation tracking
Why ScyllaDB:
Efficient partitioning and TTL support
Optimal for append-only, timestamped data
Compact storage with compression
high-performance NoSQL database
What do you like best about the product?
Blazing Fast Performance: ScyllaDB handles millions of read/write operations with millisecond-level P99 latency, making it ideal for real-time applications
Highly Scalable: Easily manages terabytes to petabytes of data without compromising speed or reliability.
Cassandra-Compatible: Uses Cassandra Query Language (CQL), easing migration from Apache Cassandra.
DynamoDB API Support: Offers flexibility for developers familiar with AWS DynamoDB.
Trusted by Industry Leaders: Used by companies like Discord, Starbucks, Zillow, and Comcast for mission-critical workloads
Highly Scalable: Easily manages terabytes to petabytes of data without compromising speed or reliability.
Cassandra-Compatible: Uses Cassandra Query Language (CQL), easing migration from Apache Cassandra.
DynamoDB API Support: Offers flexibility for developers familiar with AWS DynamoDB.
Trusted by Industry Leaders: Used by companies like Discord, Starbucks, Zillow, and Comcast for mission-critical workloads
What do you dislike about the product?
Learning Curve: While powerful, ScyllaDB’s architecture may require a deeper understanding for optimal configuration.
Limited Ecosystem Compared to Giants: Though growing, its ecosystem and community are smaller than those of MongoDB or Cassandra.
Operational Complexity: Advanced features may require more hands-on tuning and monitoring.
Limited Ecosystem Compared to Giants: Though growing, its ecosystem and community are smaller than those of MongoDB or Cassandra.
Operational Complexity: Advanced features may require more hands-on tuning and monitoring.
What problems is the product solving and how is that benefiting you?
Monitoring systems
Fraud detection
Recommendation engines
Ad tech platforms
Fraud detection
Recommendation engines
Ad tech platforms
High-performance, scalable database solution for real-time applications
What do you like best about the product?
ScyllaDB offers incredibly low latency and high throughput, making it ideal for real-time applications at scale. Its compatibility with Apache Cassandra makes migration smooth, and the automatic sharding and self-tuning features significantly reduce operational overhead.
What do you dislike about the product?
The learning curve can be steep for teams unfamiliar with NoSQL databases or distributed systems. Some documentation could be more beginner-friendly, especially for operational best practices and tuning. Also, the ecosystem isn't as large as more mature alternatives, which means fewer community resources.
What problems is the product solving and how is that benefiting you?
ScyllaDB enables us to handle large volumes of real-time data with ultra-low latency, which is crucial for analytics and user-facing features that require instant feedback. It has also reduced our infrastructure costs by efficiently using available hardware while maintaining high availability and performance under load.
Best Database for IOT Data Analytics
What do you like best about the product?
ScyllaDB is an excellent option for IoT data ingestion because it efficiently manages large volumes of high-throughput, low-latency tasks. When vast amounts of sensor data are being loaded continuously, often in real time, ScyllaDB's shard-per-core architecture ensures that performance remains consistent, avoiding the slowdowns that typically plague traditional databases. Plus, the strength of its community and the wealth of learning resources available are definitely worth mentioning.
What do you dislike about the product?
ScyllaDB lacks native support for complex secondary indexes and full-text search, which can limit flexibility in some querying patterns. Otherwise everything just works flawlessly.
What problems is the product solving and how is that benefiting you?
ScyllaDB manages the high-intensive workload of ingesting and querying vast amounts of IoT telemetry data with low latency and high availability. By effectively managing time-series workloads at scale, it provides real-time analytics and monitoring with no performance degradation. This makes us able to receive prompt insights and consistent downstream processing.
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