131–140 of 140 posts
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What about https://github.com/meilisearch/MeiliSearch ?
I am looking into this. Do you have experience with it?
Sorry to hijack the thread but can anyone suggest alternatives to the 'search' side of Elasticsearch? I haven't been following the topic and there's probably new and interesting developments like ClickHouse is for logging.
1. Toshi https://github.com/toshi-search/Toshi (Rust, 3.1k stars)
2. Tantivy https://github.com/tantivy-search/tantivy (Rust, 4.5k stars)
3. PISA https://github.com/pisa-engine/pisa (C++, 486 stars)
4. Bleve https://github.com/blevesearch/bleve (Go, 7.4k stars)
5. Sonic https://github.com/valeriansaliou/sonic (Rust, 10.9k stars)
6. Partial comparison https://mosuka.github.io/search-benchmark-game/ (tantivy Vs lucene Vs pisa Vs bleve)
7. Bayard https://github.com/bayard-search/bayard (Rust, on top of Tantivy, 1.4k stars)
8. Blast https://github.com/mosuka/blast (Go, on top of Bleve, 930 stars)
Algolia alternatives with some compatibility
1. MeiliSearch https://github.com/meilisearch/MeiliSearch (Rust, 12.4k stars)
2. typesense https://github.com/typesense/typesense (C++, 5.1k stars)
Also wanted to share my overall positive experience with Clickhouse. UPSIDES * started a 3-node cluster using the official Docker images super quickly * ingested billions of rows super fast * great compression (of course, depends on your data's characteristics) * features like https://clickhouse.tech/docs/en/engines/table-engines/merget... are amazing to see * ODBC support. I initially said "Who uses that??", but we…
Most minor of nitpicks: > timeseries-oriented database Technically it’s a column oriented database that is good at time series stuff. I only say that because I know there are some databases that are even more specialised towards timeseries and ClickHouse can do way more.
[1] https://valyala.medium.com/how-victoriametrics-makes-instant...
Almost nobody wants to use elasticsearch. People want to use kibana and put up with elasticsearch.
Sorry to hijack the thread but can anyone suggest alternatives to the 'search' side of Elasticsearch? I haven't been following the topic and there's probably new and interesting developments like ClickHouse is for logging.
https://github.com/meilisearch/MeiliSearch gets a lot of traction recently. There are also Sphinx and its fork https://manticoresearch.com/ - very lightweight and fast.
The beauty of pointing it to your mysql tables and getting fulltext-via-api on the other side was quite nice.
Sorry to hijack the thread but can anyone suggest alternatives to the 'search' side of Elasticsearch? I haven't been following the topic and there's probably new and interesting developments like ClickHouse is for logging.
FWIW... 1. Toshi https://github.com/toshi-search/Toshi (Rust, 3.1k stars) 2. Tantivy https://github.com/tantivy-search/tantivy (Rust, 4.5k stars) 3. PISA https://github.com/pisa-engine/pisa (C++, 486 stars) 4. Bleve https://github.com/blevesearch/bleve (Go, 7.4k stars) 5. Sonic https://github.com/valeriansaliou/sonic (Rust, 10.9k stars) 6. Partial comparison https://mosuka.github.io/search-benchmark-game/ (tantivy Vs…
Sentry.io is using ClickHouse for search, with an API they built on top of it to make it easier to transition if need be. They blogged about it at the time they adopted it: https://blog.sentry.io/2019/05/16/introducing-snuba-sentrys-...
I think it's an unfair comparison, notably because: 1) Clickhouse is rigid-schema + append-only - you can't simply dump semi-structured data (csv/json/documents) into it and worry about schema (index definition) + querying later. The only clickhouse integration I've seen up close had a lot of "json" blobs in it as a workaround, which cannot be queried with the same ease as in ES. 2) Clickhouse scalability is not as s…
Kibana is just messy. Their demos don't show any actionable intelligence but just dumps data in various ways and the interface doesn't look focused. It feels painful to deal with it daily.
Almost nobody wants to use elasticsearch. People want to use kibana and put up with elasticsearch.
I don't buy this.
It's just a mess of data dumps and it's not exactly providing focused experience. You need to take a full month to show what you want comfortably.
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what happens when your data doesn't fit in a single node anymore?
There's replication in ClickHouse and you can just shove reads off to one of them if you'd like. From a backup/safety standpoint that's important, but I think there are other options besides just replicas, of course. From an operations standpoint, however, ClickHouse is ridiculously efficient at what it does. You can store tens of billions, probably trillions of records on a single node machine. You can query at tens…