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.
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Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.
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RavenDB
RavenDB is a pioneering NoSQL Document Database. It is fully transactional (ACID across your database and within your cluster). Our open-source distributed database has high availability and high performance, with minimal administration. It is an all-in-one database that is easy to use. This reduces the need to add on tools or support for developers to increase developer productivity and speed up your project's production.
In minutes, you can create and secure a data cluster and deploy it in the cloud, on-premise, or in a hybrid environment. RavenDB offers a Database as a Service, which allows you to delegate all database operations to us, so you can concentrate on your application. RavenDB's built-in storage engine Voron can perform at speeds of up to 1,000,000 reads per second and 150,000 write per second on a single node. This allows you to improve your application's performance by using simple commodity hardware.
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Hazelcast Jet
Hazelcast Jet offers enhanced application performance at scale, making it easier than ever to develop lightning-fast applications. Our platform provides access to a scalable, shared RAM pool across multiple computers in a cluster. As the industry's most thorough in-memory computing solution, it combines the fastest in-memory data grid with cutting-edge high-speed event processing, all accessible through the cloud. Hazelcast empowers you to create new data-enabled applications that can drive significant business impact, provided they meet the urgent demands of modern enterprises. With Hazelcast, you can utilize the shared RAM pool across a cluster to ensure your applications run at peak speed. The distributed architecture of Hazelcast guarantees redundancy, ensuring continuous cluster uptime and the availability of data for even the most resource-intensive applications. As capacity scales smoothly in response to demand, performance and availability remain uncompromised. Additionally, Hazelcast's in-memory solutions work alongside traditional databases, offering speeds that are exponentially greater. Ultimately, Hazelcast enables organizations to harness the full potential of real-time data processing, positioning them for success in a competitive landscape.
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