{"id":110625,"date":"2023-10-05T15:10:13","date_gmt":"2023-10-05T13:10:13","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/vypusk-victoriametrics-1-94-subd-dlya-postroeniya-sistem-monitoringa"},"modified":"2023-10-05T15:10:13","modified_gmt":"2023-10-05T13:10:13","slug":"vypusk-victoriametrics-1-94-subd-dlya-postroeniya-sistem-monitoringa","status":"publish","type":"post","link":"https:\/\/prohoster.info\/en\/blog\/news\/vypusk-victoriametrics-1-94-subd-dlya-postroeniya-sistem-monitoringa","title":{"rendered":"Release of VictoriaMetrics 1.94, a DBMS for building monitoring systems.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

The release of the VictoriaMetrics platform 1.94.0 is available, providing a database management system (DBMS) for storing and processing time series data (where a record comprises time and a set of corresponding values, for example, obtained through periodic polling of sensor states or metric collection), optimized for monitoring tasks. The project competes with solutions like InfluxDB, TimescaleDB, Thanos, Cortex, and Uber M3, offering higher performance. The DBMS can be used as a long-term data store connected to Prometheus and Grafana, as well as a transparent replacement for InfluxDB. The code is written in Go and distributed under the Apache 2.0 license. <\/p>\n

In performance tests, VictoriaMetrics outperforms InfluxDB and TimescaleDB in executing data insertion and query operations by up to 20 times, consuming 10 times less RAM than InfluxDB and 7 times less than Prometheus, Thanos, and Cortex when handling millions of unique time series. Storing data in a compressed format allows for 7 times more records to fit in the same storage space compared to Prometheus, Thanos, and Cortex, and 70 times more compared to TimescaleDB. There are specific optimizations for storage with high latency and low I\/O operation intensity (such as hard drives and cloud storage from AWS, Google Cloud, and Microsoft Azure). <\/p>\n

The DB is packaged as a single executable file with minimal settings provided via the command line upon startup. All data is stored in a single directory specified at launch using the '-storageDataPath' flag. MetricsQL is used as the query language, an extended version of the PromQL language utilized in the Prometheus monitoring system. In addition to continuously processing incoming data, VictoriaMetrics also supports uploading previously collected historical data. <\/p>\n

Tools are provided to protect the storage integrity from data corruption, for instance, during unexpected power outages (the storage is structured as a journal-structured merge tree), as well as a simple snapshot-based backup system. Nodes of VictoriaMetrics can be combined into a horizontally scalable cluster that supports high availability mechanisms. <\/p>\n

Among the new features added in this release: <\/p>\n