11–20 of 104 posts
It sounds like they had the wrong architecture to start with and they built a database to handle it. Kudos. Most would have just thrown cache at it or fine tuned a readonly postgis database for the geoip lookups.
Without benchmarks it’s just bold claims we’ll have to ascertain.
Slightly meta, but I find its a good sign that we're back to designing and blogging about in-house data storage systems/ Query engines again. There was an explosion of these in the 2010's which seemed to slow down/refocus on AI recently.
They're not open sourcing it though?
Doesn't sound like it, but it's a nice writeup of the tools they stitched together. For someone to copy and open source... hopefully :)
Both https://typesense.org/ and https://duckdb.org/ (with their spatial plugin) are excellent geo performance wise, the latter now seems really production ready, especially when the data doesn’t change that often. Both fully open source including clustered/sharded setups.
No affiliation at all, just really happy camper.
It’s interesting as someone in the search space how many companies are aiming to “replace Elasticsearch”
In my experience, the care and feeding that goes into an Elastic Search cluster feels like it's often substantially higher than that involved in the primary data store, which has always struck me as a little odd (particularly in cases where the primary data store is an RDBMS). I'd be very happy to use simpler more bulletproof solutions with a subset of ES's features for different use cases.
The one issue I remember is: On ES 5 we once had an issue early on where it regularly went down, turns out that some _very long_ input was being passed into the search by some scraper and killed the cluster.
Slightly meta, but I find its a good sign that we're back to designing and blogging about in-house data storage systems/ Query engines again. There was an explosion of these in the 2010's which seemed to slow down/refocus on AI recently.
Is it good? What's left to innovate on in this space? I don't really want experimental data stores. Give me something rock solid.
Especially in the context of embedding search, which this article is also trying to do. We need database that can efficiently store/query high-dimensional embeddings, and handle the nuance of real-world applications as well such as filtered-ANN. There is a ton of innovation in this space and it's crucial to powering the next generation architectures of just about every company out there. At this point, data-stores are becoming a bottleneck for serving embedding search and I cannot understate that advancements in this are extremely important for enabling these solutions. This is why there is an explosion of vector-databases right now.
This article is a great example of where the actual data-providers are not providing the solutions companies need right now, and there is so much room for improvement in this space.
Bit thin on details and not looking like they’ll open source it, but if someone clicked the post because they’re looking for their “replace ES” thing: Both https://typesense.org/ and https://duckdb.org/ (with their spatial plugin) are excellent geo performance wise, the latter now seems really production ready, especially when the data doesn’t change that often. Both fully open source including clustered/sharded setu…
It’s interesting as someone in the search space how many companies are aiming to “replace Elasticsearch”
Memory-mapping lets us get pretty far, even with global coverage. We are always able to add more RAM, especially since we're running in the cloud.
Backfills and data updates are also trivial and can be performed in an "immutable" way without having to reason about what's currently in ES/Mongo, we just re-index everything with the same binary in a separate node and ship the final assets to S3.
Bit thin on details and not looking like they’ll open source it, but if someone clicked the post because they’re looking for their “replace ES” thing: Both https://typesense.org/ and https://duckdb.org/ (with their spatial plugin) are excellent geo performance wise, the latter now seems really production ready, especially when the data doesn’t change that often. Both fully open source including clustered/sharded setu…
A while ago I tried to create something that has duckdb + its spatial and SQLite extensions statically linked and compiled in. I realized I was a bit in over my head when my build failed because both of them required SQLite symbols but from different versions.