Focusing on delivering "Easy-first Unified Communications", Yeastar P-Series Phone System offers companies of all sizes with a complete package for calls, video, messaging, and integrations, out of the box.
Available in the Appliance, Software, and Cloud Editions, P-Series provides flexible deployment options, allowing you to have it sited on-premises or in the cloud. Balancing costs and future growth, it requires a lower total cost of ownership, less training, and fewer management efforts. The ease of use and future-proof adaptability are paramount.
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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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TimescaleDB
TimescaleDB brings the power of PostgreSQL to time-series and event data at any scale. It extends standard Postgres with features like automatic time-based partitioning (hypertables), incremental materialized views, and native time-series functions, making it the most efficient way to handle analytical workloads. Designed for use cases like IoT, DevOps monitoring, crypto markets, and real-time analytics, it ingests millions of rows per second while maintaining sub-second query speeds. Developers can run complex time-based queries, joins, and aggregations using familiar SQL syntax — no new language or database model required. Built-in compression ensures long-term data retention without high storage costs, and automated data management handles rollups and retention policies effortlessly. Its hybrid storage architecture merges row-based performance for live data with columnar efficiency for historical queries. Open-source and 100% PostgreSQL compatible, TimescaleDB integrates with Kafka, S3, and the entire Postgres ecosystem. Trusted by global enterprises, it delivers the performance of a purpose-built time-series system without sacrificing Postgres reliability or flexibility.
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Baidu AI Cloud Stream Computing
Baidu Stream Computing (BSC) offers the ability to process real-time streaming data with minimal latency, impressive throughput, and high precision. It seamlessly integrates with Spark SQL, allowing for complex business logic to be executed via SQL statements, which enhances usability. Users benefit from comprehensive lifecycle management of their streaming computing tasks. Additionally, BSC deeply integrates with various Baidu AI Cloud storage solutions, such as Baidu Kafka, RDS, BOS, IOT Hub, Baidu ElasticSearch, TSDB, and SCS, serving as both upstream and downstream components in the stream computing ecosystem. Moreover, it provides robust job monitoring capabilities, enabling users to track performance indicators and establish alarm rules to ensure job security, thereby enhancing the overall reliability of the system. This level of integration and monitoring makes BSC a powerful tool for businesses looking to leverage real-time data processing effectively.
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