My timeseries is slow when I use many columns

Symptoms

You are using a timeseries that has many different columns (more than 1,000). The insert performance of this timeseries is considerably worse than a timeseries with few columns.

Cause

QuasarDB implements MVCC transactions to ensure data consistency. References of these transactions are maintained in a map with O(log n) complexity. By using a large amount of columns, the upkeeping of th data structure that maintains the transaction references becomes a bottleneck.

Resolution

Unlike other databases, QuasarDB isn't limited to a certain amount of timeseries and we encourage the use of many different timeseries; millions of timeseries is appropriate for many use cases. If you experience performance issues due to a large amount of different columns, we recommend to explore modeling your data this way, as it usually results in datasets with lower cardinality.

References

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