4 ms·

Open-source Time-Series Benchmarking Suite: https://github.com/timescale/tsbs https://github.com/timescale/tsbs InfluxDB: https://blog.timescale.com/blog/wh

by mfreed 7y ago

Open-source Time-Series Benchmarking Suite: https://github.com/timescale/tsbs https://github.com/timescale/tsbs InfluxDB: https://blog.timescale.com/blog/what-is-high-cardinality-how-do-time-series-databases-influxdb-timescaledb-compare/ https://blog.timescale.com/blog/what-is-high-cardinality-how... https://blog.timescale.com/blog/timescaledb-vs-influxdb-for-time-series-data-timescale-influx-sql-nosql-36489299877/ https://blog.timescale.com/blog/timescaledb-vs-influxdb-for-... Cassandra: https://blog.timescale.com/blog/time-series-data-cassandra-vs-timescaledb-postgresql-7c2cc50a89ce/ https://blog.timescale.com/blog/time-series-data-cassandra-v... MongoDB: https://blog.timescale.com/blog/how-to-store-time-series-data-mongodb-vs-timescaledb-postgresql-a73939734016/ https://blog.timescale.com/blog/how-to-store-time-series-dat...

AdamProut 7y ago
I think the ask was for comparisons against traditional analytics databases (redshift, Vertica, etc.). Columnstores are substantially faster for table scans + aggregations then rowstores (and they use a lot less storage) [1]. [1] http://db.csail.mit.edu/projects/cstore/vldb.pdf http://db.csail.mit.edu/projects/cstore/vldb.pdf
einpoklum 7y ago
Yes, it's just like I thought. You're comparing against transaction-oriented DBMSes, or ones which handle documents rather than tabular data (and hence slow on tabular data). One possible exception is InfluxDB - I'm not familiar enough with it. Anyway, try running TSBS on columnar DBMSes like Actian VectorH, Vertica, SAP HANA etc. ClickHouse may also be relevant; they don't support any possible schema, but it may be enough to run TSBS.
- oddtodd 7y ago
  At the end of 2018 Altinity benchmarked ClickHouse against the TSBS and documented it. https://www.altinity.com/blog/clickhouse-for-time-series https://www.altinity.com/blog/clickhouse-for-time-series
- softwarelimits 7y ago
  Thank you very much for your valuable input - it is very important that people understand the differences and look into this! Performance comparisons to the candidates you named would be very interesting to see. Downvoters: you should be happy that people with more knowledge than the average javascript-aws-webdevops-guy that is needed to operate a startup invest time to inform you about alternatives you might not know about. Also it is important to keep this site attractive to people that have a different opinions and experiences - do not do that trump thing! Thanks! Of course, for each claim replicable facts are needed.
- XuMiao 7y ago
  I am curious about that too. As a separate topic, if the operational dbs can be compatible with parquet type storage (backup and restore), the offline analytics and machine learning would be seamlessly integrated together. Offline analytics usually can simplify online analytics. Discovering new dimensions, normalization/denormalization, and optimization of indices and partitions. Operational dbs shouldn't have to stress themselves at the gunpoint.
- RobAtticus 7y ago
  We're happy to take pull requests for new databases, we have so far from Clickhouse, CrateDB, and SiriDB (and one pending). We've tried to make it relatively easy for new databases to hook in. We usually implement ones that we hear about a lot from customers, and so far those haven't come up a ton. We'll keep it in mind though as we look to keep adding new ones.

by mfreed 7y ago

AdamProut 7y ago

I think the ask was for comparisons against traditional analytics databases (redshift, Vertica, etc.). Columnstores are substantially faster for table scans + aggregations then rowstores (and they use a lot less storage) [1]. [1] http://db.csail.mit.edu/projects/cstore/vldb.pdf http://db.csail.mit.edu/projects/cstore/vldb.pdf

einpoklum 7y ago

Yes, it's just like I thought. You're comparing against transaction-oriented DBMSes, or ones which handle documents rather than tabular data (and hence slow on tabular data). One possible exception is InfluxDB - I'm not familiar enough with it. Anyway, try running TSBS on columnar DBMSes like Actian VectorH, Vertica, SAP HANA etc. ClickHouse may also be relevant; they don't support any possible schema, but it may be enough to run TSBS.

oddtodd 7y ago
At the end of 2018 Altinity benchmarked ClickHouse against the TSBS and documented it. https://www.altinity.com/blog/clickhouse-for-time-series https://www.altinity.com/blog/clickhouse-for-time-series
softwarelimits 7y ago
Thank you very much for your valuable input - it is very important that people understand the differences and look into this! Performance comparisons to the candidates you named would be very interesting to see. Downvoters: you should be happy that people with more knowledge than the average javascript-aws-webdevops-guy that is needed to operate a startup invest time to inform you about alternatives you might not know about. Also it is important to keep this site attractive to people that have a different opinions and experiences - do not do that trump thing! Thanks! Of course, for each claim replicable facts are needed.
XuMiao 7y ago
I am curious about that too. As a separate topic, if the operational dbs can be compatible with parquet type storage (backup and restore), the offline analytics and machine learning would be seamlessly integrated together. Offline analytics usually can simplify online analytics. Discovering new dimensions, normalization/denormalization, and optimization of indices and partitions. Operational dbs shouldn't have to stress themselves at the gunpoint.
RobAtticus 7y ago
We're happy to take pull requests for new databases, we have so far from Clickhouse, CrateDB, and SiriDB (and one pending). We've tried to make it relatively easy for new databases to hook in. We usually implement ones that we hear about a lot from customers, and so far those haven't come up a ton. We'll keep it in mind though as we look to keep adding new ones.