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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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neon
Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
This sounds cool (it's not something we've built at Neon).
In case it's useful, I can clarify:
* Every Neon database is accessible over an ordinary TCP Postgres connection (as well as WebSockets and http).
* Our JavaScript serverless driver is based on node-postgres and is a drop-in replacement for it. So for JS, no rewriting is needed.
Assuming that doesn't help, do you specifically need http (rather than WebSockets), and a proxy that speaks the pg protocol?
If not, the simplest thing might be to (1) use Neon, or run a WebSocket proxy next to your own database (e.g. https://github.com/neondatabase/wsproxy); and (2) find/write a similar WebSocket proxy, but in reverse — i.e. one that listens out for TCP/socket connections and tunnels them over WebSockets — to run next to the agents.
Here is the actual package used [1]. I thought it would have been similar to serverless-pg[2] with initiation outside the handler as with the node implementation. Any insights into how they achieve connection caching (similar to pooling?) on the edge?
[1]: https://github.com/neondatabase/serverless
Well, the data is absolutely not ephemeral: it's safely tucked away in S3.
But to crib from https://neon.tech, you might choose Neon because it's scalable, cost-effective, and needs no admin. Or you might choose it for its copy-on-write branching and point-in-time recovery, all open-source, and all on top of the solid, performant, feature-rich foundation that is Postgres. :)