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Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series:
1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases.
2. Specialized codecs like Gorilla[3], DoubleDelta[4], and FPC[5] lose to simply using ZSTD[6] compression in most cases, both in compression ratio and in performance.
3. Specialized time-series DBMS like InfluxDB or TimescaleDB lose to general-purpose relational OLAP DBMS like ClickHouse [7][8][9].
[1] https://clickhouse.com/blog/optimize-clickhouse-codecs-compr...
[2] https://github.com/ClickHouse/ClickHouse
[3] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[4] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[5] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[6] https://github.com/facebook/zstd/
[7] https://arxiv.org/pdf/2204.09795.pdf "SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things" (2022)
[8] https://gitlab.com/gitlab-org/incubation-engineering/apm/apm... https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
[9] https://www.sciencedirect.com/science/article/pii/S187705091...
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Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series:
1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases.
2. Specialized codecs like Gorilla[3], DoubleDelta[4], and FPC[5] lose to simply using ZSTD[6] compression in most cases, both in compression ratio and in performance.
3. Specialized time-series DBMS like InfluxDB or TimescaleDB lose to general-purpose relational OLAP DBMS like ClickHouse [7][8][9].
[1] https://clickhouse.com/blog/optimize-clickhouse-codecs-compr...
[2] https://github.com/ClickHouse/ClickHouse
[3] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[4] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[5] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[6] https://github.com/facebook/zstd/
[7] https://arxiv.org/pdf/2204.09795.pdf "SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things" (2022)
[8] https://gitlab.com/gitlab-org/incubation-engineering/apm/apm... https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
[9] https://www.sciencedirect.com/science/article/pii/S187705091...
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-
Interesting to match with the observations from the practice of using ClickHouse[1][2] for time series:
1. Reordering to SOA helps a lot - this is the whole point of column-oriented databases.
2. Specialized codecs like Gorilla[3], DoubleDelta[4], and FPC[5] lose to simply using ZSTD[6] compression in most cases, both in compression ratio and in performance.
3. Specialized time-series DBMS like InfluxDB or TimescaleDB lose to general-purpose relational OLAP DBMS like ClickHouse [7][8][9].
[1] https://clickhouse.com/blog/optimize-clickhouse-codecs-compr...
[2] https://github.com/ClickHouse/ClickHouse
[3] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[4] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[5] https://clickhouse.com/docs/en/sql-reference/statements/crea...
[6] https://github.com/facebook/zstd/
[7] https://arxiv.org/pdf/2204.09795.pdf "SciTS: A Benchmark for Time-Series Databases in Scientific Experiments and Industrial Internet of Things" (2022)
[8] https://gitlab.com/gitlab-org/incubation-engineering/apm/apm... https://gitlab.com/gitlab-org/incubation-engineering/apm/apm...
[9] https://www.sciencedirect.com/science/article/pii/S187705091...
