postgres-elasticsearch-fd
quickwit
postgres-elasticsearch-fd | quickwit | |
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3 | 65 | |
- | 6,244 | |
- | 7.1% | |
- | 9.8 | |
- | 4 days ago | |
Rust | ||
- | GNU General Public License v3.0 or later |
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
postgres-elasticsearch-fd
- Full-text search engine with PostgreSQL (part 2): Postgres vs. Elasticsearch
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Postgres Full Text Search vs. the Rest
My experience with Postgres FTS (did a comparison with Elastic a couple years back), is that filtering works fine and is speedy enough, but ranking crumbles when the resulting set is large.
If you have a large-ish data set with lots of similar data (4M addresses and location names was the test case), Postgres FTS just doesn't perform.
There is no index that helps scoring results. You would have to install an extension like RUM index (https://github.com/postgrespro/rum) to improve this, which may or may not be an option (often not if you use managed databases).
If you want a best of both worlds, one could investigate this extensions (again, often not an option for managed databases): https://github.com/matthewfranglen/postgres-elasticsearch-fd...
Either way, writing something that indexes your postgres database into elastic/opensearch is a one time investment that usually pays off in the long run.
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Lesser Known PostgreSQL Features
I used a foreign data wrapper to query elasticsearch indexes from within postgres.[0]
It pushed alot of complexity down away from higher-level app developers not familiar with ES patterns.
[0]: https://github.com/matthewfranglen/postgres-elasticsearch-fd...
quickwit
- Show HN: Search on S3 Using AWS Lambda
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Show HN: Quickwit – OSS Alternative to Elasticsearch, Splunk, Datadog
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
- Show HN: Quickwit – OSS Alternative to Datadog, Elasticsearch
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S3 Express Is All You Need
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/
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Show HN: Quickwit – Cost-Efficient OSS Search Engine for Observability
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-...
- OSS Sub-second search and analytics engine on cloud storage
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Ask HN: Who is hiring? (September 2023)
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.
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Observe your Rust application with Quickwit, Jaeger and Grafana
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.
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Quickwit 0.6.0 - Search and analytics on billions of logs with minimal hardware
Link: https://github.com/quickwit-oss/quickwit
What are some alternatives?
zombodb - Making Postgres and Elasticsearch work together like it's 2023
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
postgres-elasticsearch-fdw - Postgres to Elastic Search Foreign Data Wrapper
loki - Like Prometheus, but for logs.
ksuid - K-Sortable Globally Unique IDs
elasticsearch-py - Official Python client for Elasticsearch
tantivy - Tantivy is a full-text search engine library inspired by Apache Lucene and written in Rust
manticoresearch - Easy to use open source fast database for search | Good alternative to Elasticsearch now | Drop-in replacement for E in the ELK soon
Searchkick - Intelligent search made easy
openobserve - 🚀 10x easier, 🚀 140x lower storage cost, 🚀 high performance, 🚀 petabyte scale - Elasticsearch/Splunk/Datadog alternative for 🚀 (logs, metrics, traces, RUM, Error tracking, Session replay).
tbls - tbls is a CI-Friendly tool for document a database, written in Go.
zincsearch - ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.