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TimechoDB v1.2 Released! This update introduces new features to TimechoDB, the enterprise version of Apache IoTDB, including Views, Full-Stack Monitoring Dashboard, Multi-Level Storage, and Data Subscription.
In this article you could have an overview of the optimizations and new features of this latest release.
Highlight 1: Views
The new release now supports the Views feature, allowing users to assign different path names to the same time series. This enables different classifications and organizations of time series from various business perspectives. It enhances the efficiency and user experience of managing and querying time series in TimechoDB, while reducing the complexity of time series management and usage. The Views feature also provides enhanced computational capabilities based on the original sequences, enabling users to create a view sequence that represents the calculated value of several original sequences, thus facilitating logical computations on sequences.
Highlight 2: Full-Stack Monitoring Dashboard
A new Full-Stack Monitoring Dashboard is introduced specifically for TimechoDB operations. In addition to monitoring basic system resources such as CPU, memory, and disk, this comprehensive monitoring dashboard provides fine-grained monitoring for various submodules of TimechoDB. It covers the read and write main processes, including operational metrics, network traffic between nodes, write links, query links, consensus protocol layer, and data exchange layer. This complete and detailed monitoring dashboard not only provides extensive system operational information for operations personnel but also offers a convenient and efficient entry point for problem diagnosis, system optimization, and other monitoring-related needs.
Highlight 3: Multi-Level Storage
The Multi-Level Storage feature by upgrading the underlying storage capabilities is introduced. It supports dividing data into different tiers, such as cold, warm, and hot, based on factors like access frequency and data importance. These tiers are stored in different media, such as SSDs, mechanical hard drives, and cloud storage. The system also performs data scheduling during queries based on different tiers and media, ensuring data access speed while reducing customer data storage costs.
Highlight 4: Data Subscription
TimechoDB now includes the Data Subscription feature, which establishes a one-way data pipeline between TimechoDB and another data platform (such as IoTDB, Kafka, Flink, etc.). Through the collection, processing, and transmission of data, this feature streams a portion or all of the data from the original system to an external system at the operation level. The framework for this feature adopts a microkernel architecture design, allowing users to enhance or modify system functionality through scalable modules (plugins) without modifying the core code. This facilitates convenient management and aggregation of multi-level data.