Scylla
Scylla is a highly performant NoSQL database that provides low-latency, real-time analytics by leveraging a shared-nothing architecture and automatic tuning to ensure optimal resource utilization.
Quix enables you to sync from Apache Kafka to Scylla , in seconds.
Speak to us
Get a personal guided tour of the Quix Platform, SDK and API's to help you get started with assessing and using Quix, without wasting your time and without pressuring you to signup or purchase. Guaranteed!
Explore
If you prefer to explore the platform in your own time then have a look at our readonly environment
👉https://portal.demo.quix.io/?workspace=demo-dataintegrationdemo-prod
FAQ
How can I use this connector?
Contact us to find out how to access this connector.
Real-time data
Now that data volumes are increasing exponentially, the ability to process data in real-time is crucial for industries such as finance, healthcare, and e-commerce, where timely information can significantly impact outcomes. By utilizing advanced stream processing frameworks and in-memory computing solutions, organizations can achieve seamless data integration and analysis, enhancing their operational efficiency and customer satisfaction.
What is Scylla?
Scylla is a distributed NoSQL database designed for maximum performance and reliability at scale, with the ability to handle millions of transactions per second. It offers compatibility with Apache Cassandra, making it a robust choice for organizations that need a fast and scalable data storage solution.
What data is Scylla good for?
Scylla is ideal for use cases requiring high throughput and low latency, such as IoT data processing, real-time analytics, and time-series data applications. Its ability to scale horizontally and its efficient resource management make it suitable for handling massive volumes of data.
What challenges do organizations have with Scylla and real-time data?
Organizations may encounter challenges with Scylla and real-time data due to its complexity in managing large clusters and ensuring consistency across nodes. Fine-tuning the database for specific workloads and balancing resource utilization can also present obstacles, especially in highly dynamic environments.