Viewing profile — enordstr
enordstr
HN member- Joined
- Tue, Apr 04, 2017, 10:29 PM UTC
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About enordstr
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Recent public activity
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Comment #23921682
Another Timescale engineer here. As previously pointed out, zheap should work as a drop-in in TimescaleDB. In fact, I just tried it and it works. However, it currently requires an …
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Comment #20766133
It would be great if you could share with us how this feature has been working out for you and how we can improve it in the future.
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Comment #20765595
We talk about sharding vs. chunking in the blog post and I would put CitusDB in the former category. More specifically, TimescaleDB is focusing on time-series workloads. To handle …
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Comment #20765534
It basically boils down to deleting a bunch of files on disk. The fact that it is distributed doesn't affect efficiency too much; it is basically a delete sent to all nodes, follow…
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Comment #20761853
Blog post co-author and Timescale engineer here. Thanks for the advice. FWIW, though, TimescaleDB supports multi-dimensional partitioning, so a specific "hot" time interval is actu…
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Comment #19857512
Timescale engineer here. Just want to point out that you can also attach additional disks using tablespaces, which are fully supported on hypertables. With a few simple commands, t…
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Comment #17773314
Timescaler here. We're not blaming "PG devs". We have great respect for the PostgreSQL developers and what they are doing; so much, in fact, that we chose to base our product on Po…
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Comment #17773251
Fellow Timescaler here. Thanks for the feedback. While we do not directly compare ingestion protocol and specific features, like continuous queries and retention polices (something…
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Comment #14987630
We wouldn't do this if we didn't believe we could make a business out of it. That said, we are at a pretty early stage at this moment and are looking at many different options. As …
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Comment #14987104
Timescaler here. Although we haven't done any official announcements w.r.t. clustering, our plan is for this to be open source, like the single-node version.
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Comment #14041591
That point about irregularly spaced data (sparse) is a very insightful observation. I’d just add that a user can to some extent address that by normalization, i.e., splitting incom…
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Comment #14041365
Sounds like you’re main concern is high availability (HA) and scaling, things Cassandra certainly does well. But if you are also interested in data exploration and complex queries,…