RaimaDB
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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Maitre'D POS
Maitre'D is a POS system that offers a variety of functions and complete services. It can adapt to any environment, including family restaurants, fast food, or casual restaurants. Posera's Maitre'D POS offers a complete service and rich feature set that can be used in any environment, including fine and casual dining, hotel table service, family restaurants, and quick service. KDS (Kitchen Display System), is a system that's specifically designed for fast-food and fine dining. In a typical operation, it is common for staff to fail to communicate orders to the kitchen staff in a timely manner. To minimize problems associated with order entry, remote kitchen printers and micro-phone systems have been used. Microphone systems are dependent on the ability of kitchen staff to remember the details and quantities of all pending orders. This is a difficult task.
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BangDB
BangDB seamlessly incorporates AI, streaming capabilities, graph processing, and analytics directly within its database, empowering users to handle intricate data types like text, images, videos, and objects for immediate data processing and analysis. Users can ingest or stream various data types, process them, train models, make predictions, uncover patterns, and automate actions, facilitating applications such as IoT monitoring, fraud prevention, log analysis, lead generation, and personalized experiences. Modern applications necessitate the simultaneous ingestion, processing, and querying of diverse data types to address specific challenges effectively. BangDB accommodates a wide array of valuable data formats, simplifying problem-solving for users. The increasing demand for real-time data is driving the need for concurrent streaming and predictive analytics, which are essential for enhancing and optimizing business operations. As organizations continue to evolve, the ability to rapidly adapt to new data sources and insights will become increasingly vital for maintaining a competitive edge.
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Google Cloud Bigtable
Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads.
Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis.
Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps.
Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.
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