VictoriaMetrics is time series database management system that is designed as a storage back-end for Prometheus.


Non-Blocking Consistent

VictoriaMetrics uses their modified version of LSM tree (Logging Structure Merge Tree). All the tables and indexes on the disk are immutable once created. When it's making the snapshot, they just create the hard link to the immutable files.

Data Model

Column Family

The time series is consist of metrics and the values for corresponding timestamps. It looks like: ``` {"metric":{"__name__":"up","job":"node_exporter","instance":"localhost:9100"},"values":[0,0,0],"timestamps":[1549891472010,1549891487724,1549891503438]} ``` ``` {"metric":{"__name__":"up","job":"prometheus","instance":"localhost:9090"},"values":[1,1,1],"timestamps":[1549891461511,1549891476511,1549891491511]} ```


Inverted Index (Full Text) Log-Structured Merge Tree

VictoriaMetrics stores the data in MergeTree, which is from ClickHouse and similar to LSM. The MergeTree has particular design decision compared to canonical LSM. MergeTree is column-oriented. Each column is stored separately. And the data is sorted by the "primary key", and the "primary key" doesn't have to be unique. It speeds up the look-up through the "primary key", and gets the better compression ratio. The "parts" is similar to SSTable in LSM; it can be merged into bigger parts. But it doesn't have strict levels. The Inverted Index is built on "mergeset" (A data structure built on top of MergeTree ideas). It's used for fast lookup by given the time-series selector.


Not Supported

The design philosophy of VictoriaMetrics is that time series DBMSs do not require strict safety guarantees. That is, organizations can endure losing some recently inserted data. As such, it does not use a WAL and it delays flushing new data to disk.

Query Interface

Custom API PromQL

VictoriaMetrics provides a proprietary query language called MetricsQL that is a superset of PromQL.

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