garage VS quickwit

Take a look at GarageS3, it's a niceoption for "just an S3 server" for self hosting.

https://garagehq.deuxfleurs.fr/

I use it for self hosting.

Garage (https://garagehq.deuxfleurs.fr/) gets pretty close for object storage. It’s built with mixing high/low latency links and replication between multiple hosts. Unfortunately it’s not really built for end-users, but devs, so there’s no ui or anything like that.

> Theoretically they could swap with minio but last time we used it it was not a drop-in replacement yet.

Depends on whether AGPL v3 works for you or not (or whether you decide to pay them), I guess: https://min.io/pricing

I've actually been looking for more open alternatives, but haven't found much.

Zenko CloudServer seemed to be somewhat promising, but doesn't seem to be managed very actively: https://github.com/scality/cloudserver/issues/4986 (their Docker images on DockerHub were last updated 10 months ago, which is what the homepage links to; blog doesn't seem active since 2019, forums don't have much going on, despite some action on GitHub still)

There was also Garage, but that one is also AGPL v3: https://garagehq.deuxfleurs.fr/

The closest I got was discovering that SeaweedFS has an S3 compatible mode: https://github.com/seaweedfs/seaweedfs

Ah, you should check out Garage (https://garagehq.deuxfleurs.fr/) for a self-hosted, cluster-y API of S3

I'm a big fan of Garage[1], which is a dead-simple S3 drop-in that you can host on your own drives. It's designed for consumer hardware with shitty internet in-between nodes.

[1]:https://garagehq.deuxfleurs.fr/

One more thing we are also proud of: a bunch of our users is using the object storage Garage, this OSS project looks really promising, and we really cherish the OSS for this kind of unexpected combination.

- Another nice comment seen on HN « it seems to be very easy to run, not very IO intensive, and running fine on a single node with modest hardware with >2 billion log rows. It has a really cool dynamic schema feature too.» [9]

Fun fact: at least 4 users are using Garage[10] as the object storage, this OSS project looks really promising and made the HN front page a few months ago[11], we really cherish the OSS for this kind of unexpected combination.

Any feedback positive/negative always greatly appreciated here!

[0] Quickwit repo: https://github.com/quickwit-oss/quickwit

[1] Searching the web under 1000$/month: https://news.ycombinator.com/item?id=27074481

[2] Chitchat gossip library: https://github.com/quickwit-oss/chitchat

[3] Columnar format: https://github.com/quickwit-oss/tantivy/tree/main/columnar

[4] Tantivy library: https://github.com/quickwit-oss/tantivy/

[5] Whichlang library: https://github.com/quickwit-oss/whichlang

[6] GitHub Archive demo in terminal: https://www.youtube.com/watch?v=SNq3bARRlDI

[7] Indexing performance: https://twitter.com/fulmicoton/status/1638016949459488768

[8] https://twitter.com/arnonrgo/status/1645429632303235073?s=20

[9] https://news.ycombinator.com/item?id=35742544

[10] Garage object storage: https://garagehq.deuxfleurs.fr/

[11] https://news.ycombinator.com/item?id=33853539

On the technical side, garage (https://garagehq.deuxfleurs.fr/) does multi master replication by default, so is probably better for this use case. Still with S3 API.

You are looking for garage.

Hi folks, Quickwit cofounder here.

We started Quickwit 3 years ago with a POC, "Searching the web for under $1000/month" (see HN discussions [0]), with the goal of making a robust OSS alternative to Elasticsearch / Splunk / Datadog.

We have reached a significant milestone with our latest release (0.7) [1], as we have witnessed users of the nightly version of Quickwit deploy clusters with hundreds of nodes, ingest hundreds of terabytes of data daily, and enjoy considerable cost savings.

To give you a concrete example, one company is ingesting hundreds of terabytes of logs daily and migrating from Elasticsearch to Quickwit. They divided their compute costs by 5x and storage costs by 2x while increasing retention from 3 to 30 days. They also increased their durability, accuracy with exactly-once semantics thanks to the native Kafka support, and elasticity.

The 0.7 release also brings better integrations with the Observability ecosystem: improvements of the Elasticsearch-compatible API and better support of OpenTelemetry standards, Grafana, and Jaeger.

Of course, we still have a lot of work to be a fully-fledged observability engine, and we would love to get some feedback or suggestions.

To give you a glance at our 2024 roadmap, we planned to focus on Kibana/OpenDashboard integration, metrics support, and pipe-based query language.

[0] Searching the web for under $1000/month: https://news.ycombinator.com/item?id=27074481

[1] Release blog post: https://quickwit.io/blog/quickwit-0.7

[2] Open Source Repo: https://github.com/quickwit-oss/quickwit

[3] Home Page: https://quickwit.io

We tested S3 Express for our search engine quickwit[0] a couple of weeks ago.

While this was really satisfying on the performance side, we were a bit disappointed by the price, and I mostly agree with the article on this matter.

I can see some very specific use cases where the pricing should be OK but currently, I would say most of our users should just stay on the classic S3 and add some local SSD caching if they have a lot of requests.

[0] https://github.com/quickwit-oss/quickwit/

Hi HN, I’m one of the builders of Quickwit, a cloud-native OSS search engine for observability. As of 2023, we support logs and traces, metrics will come in 2024.

You know the pitch: while software like Datadog or Splunk are great, they often comes with hefty price tags. Our mission is to offer an affordable alternative. So we’ve built Quickwit, we’ve made it compatible with the observabilty ecosystem (OpenTelemetry, Jaeger, Grafana) and above all, we’ve made it cost-efficient / “easy” to scale (well it’s never easy to scale to petabytes..).

To give you a glance at the engine performance I made a benchmark on the GitHub Archive dataset, 23 TB of events, here are the main observations:

Indexing: costs $2 per ingested TB. With 4CPU, throughput is at 20MBs However, you'll observe > 30MB throughput on simpler datasets, like logs and traces.

Search: a typical query costs $0.0002 per TB (considering both CPU time and GET request costs). Using 8CPU, a simple query on 23TB is achieved in under a second.

Storage: on S3, it costs $8 per ingested TB per month on the GitHub Archive dataset. With logs and traces, you might see costs around $5/ingested TB due to a 2x better compression ratio.

I'm eager to get your thoughts on this!

Benchmark: https://quickwit.io/blog/benchmarking-quickwit-engine-on-an-...

Github repo: https://github.com/quickwit-oss/quickwit/

Website: https://quickwit.io/

- On S3, it costs $8 per ingested TB per month on the GitHub Archive dataset. With logs and traces, you might see costs around $4/ingested TB due to a 2x better compression ratio.

I'm eager to get your thoughts on this!

[0] Benchmark: https://quickwit.io/blog/benchmarking-quickwit-engine-on-an-...

Quickwit (https://quickwit.io/) | Paris, France | Onsite and remote (based in Europe) | Full-time

The company is fully remote but we also have a small office in Paris. We prefer candidates based in Europe but can make exceptions for the right profiles.

- Senior Software Engineer 80-110k€ + 0.25-1% equity based on experience.

    We’re looking for a senior software engineer to contribute to [Quickwit](https://github.com/quickwit-oss/quickwit), our open-source search and analytics engine. We have an ambitious roadmap for the next 18 months (performance optimization, distributed storage, support for SQL, query optimizer, revamp of our execution engine, etc.), and this is a great opportunity to shape the future of Quickwit while tackling fun and challenging problems in the field of distributed databases.

In our latest blog post, we walk you through the steps of instrumenting your Rust application and monitoring the performance on Grafana using Quickwit + Jaeger.

Link: https://github.com/quickwit-oss/quickwit