Re:MetricsDB: TimeSeries Database for storing metrics at Twi...
by manigandham on Wednesday June 17, 2020 @07:35AM
(#23550200)
Modern column-oriented relational data warehouses will handle time-series data fine in 95% of cases.
What "time-series" databases offer is more functionality around time being a primary component of the data. For example, automatic partitoning/sharding on time, various date handling techniques, better bucketing/gap filling/smoothing functions, data retention policies based on time, automatic rollups and aggregations, etc.
Some have custom data stores, some use key/value stores like Hbase or Cassandra, and others use relational databases. Using relational foundations offers more flexibility (like Timescale on top of Postgres) than the others like InfluxDB or OpenTSDB.
What "time-series" databases offer is more functionality around time being a primary component of the data. For example, automatic partitoning/sharding on time, various date handling techniques, better bucketing/gap filling/smoothing functions, data retention policies based on time, automatic rollups and aggregations, etc.
Some have custom data stores, some use key/value stores like Hbase or Cassandra, and others use relational databases. Using relational foundations offers more flexibility (like Timescale on top of Postgres) than the others like InfluxDB or OpenTSDB.