1,695 karma · joined October 19, 2010
But usability will be massively better. Both platforms offer various things to make developer more efficient and dev cycle shorter
For small workloads egress cost doesn’t matter. For larger - well it does.
I wish it was illegal to charge so much for egress for cloud providers.
And autoscaling works like this: https://neon.tech/docs/introduction/autoscaling
Storage is will be long term unlimited. Short term it is few terabytes - we are constantly increasing the ceiling as storage sharding improves: https://neon.tech/blog/how-we-scale-an-open-source-multi-ten...
Compute autoscales from 0 to 10CPUs per read replica with 0.25 CPU increments - you set up min and max. We give our enterprise customers larger compute sizes. And you can have A LOT of read replicas that stand up instantly.
On the other hand focus and product identity are very important for startups. So it’s only Postgres
What makes it not serverless in your opinion? This is our architecuture: https://neon.tech/docs/introduction/architecture-overview and no, you can not get the same from CloudSQL.
Happy to answer any questions here. We hope we will make this happen some time
Aurora is one of the few real innovations in the database space recognized by SIGMOD: https://sigmod.org/sigmod-awards/citations/2019-sigmod-syste...
It provides a lot of benefits to the user and also a ton more to the service provider. Specifically you don’t overprovision storage or compute. Plus at least theoretically you can provide invite IO throughput at the storage level.
There has been a couple more iterations on the design since. Microsoft separated transaction log from storage: https://www.microsoft.com/en-us/research/uploads/prod/2019/0...
Neon added an object store and branches so you can integrate backups and add a Time Machine.
PolarDB separated memory from compute - this makes serverless compute more nimble and unties memory and CPU.
One solution could be integrating duckdb in a similar way as pgvector. You need to map duckdb storage to Postgres storage and reuse duckdb query processor. I believe it's the fastest way to get Postgres to have competitive columnstores.
I assume that's DataFusion speed. What's the plan to improve upon it?
We are also iterating over prices - we were purely consumption before and realized that we need to offer $19 pain plan to start based on the value our customers get. This is in line for what other devplatform charge for using their services.
\dt+ translates to
SELECT schemaname, tablename, tableowner, tablespace, pg_size_pretty(pg_total_relation_size(quote_ident(schemaname) || '.' || quote_ident(tablename))) AS total_size FROM pg_tables ORDER BY pg_total_relation_size(quote_ident(schemaname) || '.' || quote_ident(tablename)) DESC;
Internally we are measuring the number of projects under 5 min in the last 30 days and it's been lower double digits over 700K+ total databases under management.
A TON of effort is going there, twice a week standups, tightening our processes and quality across the board, a standing item in our monthly board meetings. While stability is black and white, what goes into delivering it is a long tail of small and large improvement and a major team effort.
We will also update the status page soon.
We are rethinking this, please stay tuned
Our storage tech is amazing :)
And written in Rust for extra fun and profit