Compare RaimaDB vs. Voldemort

RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times. RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.

Voldemort does not function as a relational database, as it does not aim to fulfill arbitrary relations while adhering to ACID properties. It also does not operate as an object database that seeks to seamlessly map object reference structures. Additionally, it does not introduce a novel abstraction like document orientation. Essentially, it serves as a large, distributed, durable, and fault-tolerant hash table. For applications leveraging an Object-Relational (O/R) mapper such as ActiveRecord or Hibernate, this can lead to improved horizontal scalability and significantly enhanced availability, albeit with a considerable trade-off in convenience. In the context of extensive applications facing the demands of internet-level scalability, a system is often comprised of multiple functionally divided services or APIs, which may handle storage across various data centers with their own horizontally partitioned storage systems. In these scenarios, the possibility of performing arbitrary joins within the database becomes impractical, as not all data can be accessed within a single database instance, making data management even more complex. Consequently, developers must adapt their strategies to navigate these limitations effectively.