Yandex Managed Service for Redis vs. Dragonfly

In mere minutes, you can establish a fully operational cluster that is tailored to your needs. The configurations for the database are automatically optimized according to the cluster size you choose. If your cluster experiences increased demand, you can quickly add new servers or enhance the capacity of existing ones without any hassle. Redis employs a key-value data storage system, which supports a variety of formats including strings, arrays, dictionaries, sets, and bitmasks. Functioning mainly in RAM, Redis is particularly suited for applications requiring swift responses or for handling a large number of operations on relatively small datasets. To ensure the safety of your database content, GPG encryption is used for backups, and data protection measures comply with local laws, GDPR, and ISO standards. Moreover, you have the option to set a time limit for the Yandex Managed Service for Redis to automatically remove data, which assists in minimizing storage costs. This functionality not only enhances resource management but also upholds compliance and security measures effectively. Overall, this streamlined approach makes it easier to maintain a balance between performance and regulatory requirements.

Dragonfly acts as a highly efficient alternative to Redis, significantly improving performance while also lowering costs. It is designed to leverage the strengths of modern cloud infrastructure, addressing the data needs of contemporary applications and freeing developers from the limitations of traditional in-memory data solutions. Older software is unable to take full advantage of the advancements offered by new cloud technologies. By optimizing for cloud settings, Dragonfly delivers an astonishing 25 times the throughput and cuts snapshotting latency by 12 times when compared to legacy in-memory data systems like Redis, facilitating the quick responses that users expect. Redis's conventional single-threaded framework incurs high costs during workload scaling. In contrast, Dragonfly demonstrates superior efficiency in both processing and memory utilization, potentially slashing infrastructure costs by as much as 80%. It initially scales vertically and only shifts to clustering when faced with extreme scaling challenges, which streamlines the operational process and boosts system reliability. As a result, developers can prioritize creative solutions over handling infrastructure issues, ultimately leading to more innovative applications. This transition not only enhances productivity but also allows teams to explore new features and improvements without the typical constraints of server management.