Ok everything open source was not good enough. Please make a simple benchmark. Without it, it is so hard to make decisions
M3DB, a distributed timeseries database
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Re: M3DB, a distributed timeseries database
#12I get Uber is huge. But honestly, there was nothing out there that could fulfill there use case? Cassandra, ElasticSearch, Influx, etc.? I might be completely wrong, but I just highly doubt that.
It's a database for a metric platform.
Think of OpenTSDB and Prometheus. Or for a better comparison think of Thanos https://thanos.io/
As to whether they could fulfil Uber's needs, the thing about scale (real massive scale - I work at Cloudflare) is that everything breaks in weird ways according to your specific uses of a technology. The things listed above work for companies, until they don't. There's few things that seem to truly work at every scale, Kafka and ClickHouse come to mind for wholly different use cases than a time series database.
Re: M3DB, a distributed timeseries database
#13admins/mods: this needs an apostrophe to turn it into "Uber's M3DB".
For anyone who's never heard of M3DB, and lives in a place where Uber doesn't operatore or is even banned (and so isn't part of daily life or conversation) "Ubers" might just as easily be some db researcher affiliated with the university of who knows where showing off something they came up with last summer and got a grant for.
Re: M3DB, a distributed timeseries database
#14Does "Time Series Database" mean anything technical, or is this just some Uber marketing? In statistics, time series has a technical meaning.
A db that backs lots of time based graphs. They generally hit some pathological cases for general dbs. Frequent write of small data, most recent time is very hot so sharding is tricky, queries generally pull lots of little bits of data in from long time ranges, resolution of past data can often be lowered, etc.
Opentsdb for instance was built on top of Hbase because implementing one naively in hbase hits tons of performance issues.
Re: M3DB, a distributed timeseries database
#15So how does this compare to e.g. Clickhouse?
Re: M3DB, a distributed timeseries database
#16Uber has started many projects that ended up getting open sourced. And many of them are now either abandoned or on life support. H3 comes to mind as something we almost ended up using but luckily avoided. These open-sourcings seem a bit like PR pieces with no guarantees of any support or evolution after being published.
It's opensource. Why should Uber give any guarantees? They are not in the business of selling software. Unless Uber is actively blocking contributions, it's not Uber's fault if no community formed around something they opensourced. As for this being a PR piece, they could have achieved the same with just a detailed blog post and no code. It looks like a expensive PR piece if they have to opensource work that took pro…
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Re: M3DB, a distributed timeseries database
#17Does "Time Series Database" mean anything technical, or is this just some Uber marketing? In statistics, time series has a technical meaning.
There many flavours of time series databases, but my understanding is that at their core they're optimised for storing and querying based on time stamp/time series data. Typically very quickly in large volumes. That's maybe the primary criteria to define a database as a time series database.
Someone could probably elaborate on this a massive amount. I'm sure there is some nuance and a lot of relevant details around how that optimization is done.
Re: M3DB, a distributed timeseries database
#18Does "Time Series Database" mean anything technical, or is this just some Uber marketing? In statistics, time series has a technical meaning.
It's not a marketing term. It's a database optimised for storing and querying time based metrics.
Uber didn't invent the term, there are a lot of existing products in market.
Question is why none of them worked for them. I have used OpenTSDB and it worked great at Mastercard scale. What issues did Uber had?
Re: M3DB, a distributed timeseries database
#19Earlier quoted context omitted.
It's opensource. Why should Uber give any guarantees? They are not in the business of selling software. Unless Uber is actively blocking contributions, it's not Uber's fault if no community formed around something they opensourced. As for this being a PR piece, they could have achieved the same with just a detailed blog post and no code. It looks like a expensive PR piece if they have to opensource work that took pro…
I agree with everything you say. But without any certainty around the roadmap, support, and longterm commitment by Uber to maintain these projects, they're nothing more than interesting repos amongst a sea of interesting repos. The way Uber brands them suggests that they're suitable for use in production environments, but so far that hasn't been the case with anything they open sourced outside a narrow envelope that…
Isn't that kind of the point of open-sourcing your internal tools? You don't want to be bothered with maintenance and support, so you're hoping that some anonymous volounteers will do that for you :)
Re: M3DB, a distributed timeseries database
#20I get Uber is huge. But honestly, there was nothing out there that could fulfill there use case? Cassandra, ElasticSearch, Influx, etc.? I might be completely wrong, but I just highly doubt that.
I can give you an ex-insiders view on this.
Uber made an early strategic decision to invest in on-premise infrastructure due to fears that either Amazon or Google would enter the on-demand market as competitors and bring their cloud infrastructure to bear and potentially squeeze us for costs. Azure wasn’t much of an option during this time. This decision limited our adoption of cloud native solutions like SpannerDB and DynamoDB. We ended up doing a lot of sharded MySQL in our own data centers instead.
This on-prem decision led to a lot challenges internally where we would adopt OSS and then have difficulty scaling it to our needs. For some tech like Kafka it worked out, and we hired Kafka contributors who helped us scale it. For other tech like Cassandra it was a pretty epic failure. I am sure more of these war stories exist that I wasn’t privy to myself.
Coupled with the fact that we were early adopters into Golang which had its own OSS ecosystem, we found that writing a lot of our own infrastructure solutions was the only viable option at our scale.
What you are seeing now is a lot of that home grown infrastructure being open sourced in big way as people who have left Uber continue to see value in investing in the tech that they worked so hard to build. There is probably a nontrivial amount of work to scale the Uber OSS down for smaller use cases but some startups are emerging to make that happen.
Source: I worked at Uber from 2015-2019 on product and platform teams and had several close colleagues in infra.