elasticsearch-py
quickwit
Our great sponsors
elasticsearch-py | quickwit | |
---|---|---|
21 | 64 | |
4,136 | 6,052 | |
0.8% | 9.6% | |
8.7 | 9.8 | |
8 days ago | 7 days ago | |
Python | Rust | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
elasticsearch-py
- Verify Connection to Elasticsearch (2021)
- An alternative to Elasticsearch that runs on a few MBs of RAM
- Help With Psort.py -> ELK
- Elastic Open Sources Their Endpoint Security Protection YARA Ruleset
-
OpenSearch – open-source search and analytics based on Apache 2.0 Elasticsearch
FD: I have a friend who works at Elastic, though he doesn't really colour my opinions of things.
> Firstly, dick moves like this: https://github.com/elastic/elasticsearch-py/pull/1623
I understand that this is unpopular, but you can make a very strong argument that it's to prevent weird errors in the future. I'm also guilty of littering my code with Asserts to ensure the universe is working fine.
The alternative is to allow it to work and then you end up with weird issues like when you connect mysql client to mariadb server (and vice-versa): https://stackoverflow.com/questions/50169576/mysql-8-0-11-er...
> Secondly, I don't buy the argument from Elastic any more. Yes, the ethical thing to do when you're making money from someone's work is at least contribute back. At the same time though, they're making money from packaging it up and selling it _as a service_. That "as a service" part is where they're making the bucks.
That's just an opinion, yes they have a service, and yes it competes with Amazon. Is it cool for Amazon to take a body of work and sell it without supporting it? Are amazon actually supporting it? Is it the same as Elastic using Lucene? (not really because Elastic submits a the majority of fixes to Lucene, but, you get it).
it's kinda gray, I'm sure Amazon thinks they're the good guy, but it's hard for me to look at Elastic as the bad guy in all this.
- Struggling reading code with type hints
-
I Don't Think Elasticsearch Is a Good Logging System
Oh man, https://github.com/elastic/elasticsearch-py/issues/1734 is a disappointing read. I know ES wants to save their business, but alienating users isn't exactly the path to success.
- Elasticsearch adding code to reject connections to OpenSearch clusters or to clusters running open source distributions of ES7
- Official Elasticsearch Python library no longer works with open-source forks
quickwit
- Show HN: Search on S3 Using AWS Lambda
-
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
-
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/
-
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
-
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.
-
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.
-
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?
searxng - SearXNG is a free internet metasearch engine which aggregates results from various search services and databases. Users are neither tracked nor profiled.
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
helm-charts
loki - Like Prometheus, but for logs.
orama - 🌌 Fast, dependency-free, full-text and vector search engine with typo tolerance, filters, facets, stemming, and more. Works with any JavaScript runtime, browser, server, service!
manticoresearch - Easy to use open source fast database for search | Good alternative to Elasticsearch now | Drop-in replacement for E in the ELK soon
qryn - qryn is a polyglot, high-performance observability framework for ClickHouse. Ingest, store and analyze logs, metrics and telemetry traces from any agent supporting Loki, Prometheus, OTLP, Tempo, Elastic, InfluxDB and many more formats and query transparently using Grafana or any other compatible client.
openobserve - 🚀 10x easier, 🚀 140x lower storage cost, 🚀 high performance, 🚀 petabyte scale - Elasticsearch/Splunk/Datadog alternative for 🚀 (logs, metrics, traces, RUM, Error tracking, Session replay).
evtx2es - A library for fast parse & import of Windows Eventlogs into Elasticsearch.
zincsearch - ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.
zeek-clickhouse
Typesense - Open Source alternative to Algolia + Pinecone and an Easier-to-Use alternative to ElasticSearch ⚡ 🔍 ✨ Fast, typo tolerant, in-memory fuzzy Search Engine for building delightful search experiences