db-benchmarks
quickwit
db-benchmarks | quickwit | |
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24 | 64 | |
111 | 6,098 | |
2.7% | 4.9% | |
4.9 | 9.8 | |
12 months ago | 6 days ago | |
PHP | Rust | |
GNU Affero General Public License v3.0 | 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.
db-benchmarks
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Dozer vs. AirByte and Elasticsearch: The Fast Lane to Data Serving Efficiency
> I decided to experiment with this setup and the NY Taxi Dataset. The initial goal was to populate ElasticSearch with ~14 million rows, loading data from a compressed parquet file of ~350 MB.
> I tried multiple times, but the operation failed continuously, due to JVM memory constraints
Here's a script https://github.com/db-benchmarks/db-benchmarks/blob/main/tes... which loads 1.7B NYC taxi ride documents into Elasticsearch.
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Meilisearch vs Manticore Search
In general, you are correct about another missing key: since we added an exception for MySQL by including two keys, we should perhaps optimize it to the maximum and add the rest as well. However, it would be better to make this more visible directly within the results then. I've created a task about it https://github.com/db-benchmarks/db-benchmarks/issues/30 . Thank you for pointing this out. If you see more issues, feel free to file them on github.
- Elastic, Loki and SigNoz – A Perf Benchmark of Open-Source Logging Platforms
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ZincSearch – lightweight alternative to Elasticsearch written in Go
> It's interesting to note that Elasticsearch and Opensearch are general purpose search engine, Solr as well. They are all powered by Lucene, the popular and performant search engine library.
Another search engine which can be considered general, is not based on Lucene and is not less powerful than Elasticsearch/Solr is Manticore Search [1]
[1]: https://github.com/manticoresoftware/manticoresearch
> I would love to see some benchmarks by category :)
I'd love too. We started this work on db-benchmarks [2] , hopefully we'll have resources to continue it. Contributions are very welcome. It's 100% opensource [3]
[2]: https://db-benchmarks.com/
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Manticore Search: Elasticsearch Alternative
Comparing full-text search engines on queries that aren't full-text search are of course slow, these tests should be adapted to the proper usage of the tested DBs and not just benchmarked across the board..
Example: https://db-benchmarks.com/?cache=fast_avg&engines=elasticsea...
- No, QuestDB is not Faster than ClickHouse
- Announcing DB Benchmarks - the most fair open source database and search engines benchmarks
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110 million comments from Hacker News benchmark
Clickhouse: no tuning , just CREATE TABLE ... ENGINE = MergeTree() ORDER BY id and standard clickhouse-server docker image.
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1.1 million comments from Hacker News: small data full-text / analytics test
MySQL and Percona Server for MySQL: no tuning , just CREATE TABLE ..., FULLTEXT(story_text,story_author,comment_text,comment_author))and standard mysql docker image .
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Announcing DB Benchmarks - the most fair open source database benchmarks
https://db-benchmarks.com is a platform and a framework for making the most fair, transparent and open source database and search engines benchmarks. No more benchmarketing, because:
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?
Elasticsearch - Free and Open, Distributed, RESTful Search Engine
MeiliSearch - A lightning-fast search API that fits effortlessly into your apps, websites, and workflow
mu - maildir indexer/searcher + emacs mail client + guile bindings
loki - Like Prometheus, but for logs.
pagefind - Static low-bandwidth search at scale
elasticsearch-py - Official Python client for Elasticsearch
beir - A Heterogeneous Benchmark for Information Retrieval. Easy to use, evaluate your models across 15+ diverse IR datasets.
manticoresearch - Easy to use open source fast database for search | Good alternative to Elasticsearch now | Drop-in replacement for E in the ELK soon
ElasticPress - A fast and flexible search and query engine for WordPress.
openobserve - 🚀 10x easier, 🚀 140x lower storage cost, 🚀 high performance, 🚀 petabyte scale - Elasticsearch/Splunk/Datadog alternative for 🚀 (logs, metrics, traces, RUM, Error tracking, Session replay).
sonic - 🦔 Fast, lightweight & schema-less search backend. An alternative to Elasticsearch that runs on a few MBs of RAM.
zincsearch - ZincSearch . A lightweight alternative to elasticsearch that requires minimal resources, written in Go.