В попередній частині – AWS: знайомство з OpenSearch Service в ролі vector store – подивились на AWS OpenSearch Service взагалі, трохи розібрались з тим, як в ньому організовані дані, що таке shards та nodes, і які нам власне типи інстансів для data nodes треба. Наступний крок – створити кластер і подивитись н...| RTFM: Linux, DevOps та системне адміністрування
Знайомство з AWS OpenSearch Service в ролі vector store для AWS Bedrock Knowledge Base та планування ресурсів OpenSearch кластеру| RTFM: Linux, DevOps та системне адміністрування | De...
Today, PeerDB is pleased to announce that our target connector for Elasticsearch is now in beta. Elasticsearch is a popular search engine system underpinned by a distributed document database, and we have been seeing a lot of use cases for Elasticsea...| PeerDB Blog
Elasticsearch is a powerful, distributed search and analytics engine widely used across various applications for full-text search, log analysis, and real-time data exploration. But working with Elasticsearch via API or raw query DSL can be overwhelming, especially for those new to its schema-less structure and nested data formats. GUI clients make this process easier by... The post Best Elasticsearch GUI clients in 2025 appeared first on DronaHQ.| DronaHQ
I’ve begun to use the logstash/elasticsearch/kibana stack for processing many different types of logs, and an issue that has started […]| mcnewton's notes
In Elasticsearch, you can use wildcard in a lot of the index operations. This is very handy, but can be dangerous sometimes, e.g., when you use wildcards when deleting indexes. You may delete unintended indexes accidentally and cause serious interruptions to your business/work.| jdhao's digital space
The OpenSearch Software Foundation, part of the Linux Foundation, has released OpenSearch 3.0, with experimental GPU-accelerated vector indexing, […]| DEVCLASS
I’ve had some interesting conversations over the last few months around the three big hitters of open source search: Solr, OpenSearch and Elasticsearch. Solr is the old dog in... The post Dogfights in Open Source Search: Solr, OpenSearch and Elasticsearch appeared first on OpenSource Connections.| OpenSource Connections
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Discover how Vespa outperforms Elasticsearch in query efficiency, scalability, and operational costs, making it a robust choice for modern eCommerce search solutions.| Vespa Blog
The exposed Elasticsearch server belongs to an Indian healthcare software company that has not secured the database despite being alerted.| Hackread - Latest Cybersecurity, Tech, Crypto & Hacking News
Elasticsearch is a search server based on Apache Lucene. As a developer it is easy to use, has an expressive query DSL and all is based on JSON serialization. Often though I find myself in a position where I need to adapt queries frequently and non-trivially, say in a demonstration in front of customers or product owners. The questions are mostly similar: “what if I also filter for X”, “how does the ranking change, when I add a freshness function”, “do I get a better result if I boo...| all things considered...
Moving data from source systems like Elasticsearch to a dashboard traditionally involves a multi-step process: transferring data to a data lake, moving it into a data warehouse, and then building BI extracts and cubes for acceleration. This process can be tedious and costly. However, this entire workflow is simplified with Dremio, the Data Lakehouse Platform. Dremio enables direct serving of BI dashboards from Elasticsearch or leveraging Apache Iceberg tables in your data lake.| Dremio
Elasticsearch is a distributed search engine. One can store “documents” within “indices”, which are collections of documents. One common pattern for storing time based data is to use one index per day. E.g.: tweets-2017-01-01, tweets-2017-02-01 and so on. This makes having many indices decently common, and it also makes searching across many indices common in a single search. Elasticsearch has a query type called IndicesQuery, which lets you (among other things) optimise your query pa...| Accidentally Quadratic
I wrote a simple plugin for NZBGet that inserts download history into an ElasticSearch cluster (or node). It uses API calls rather than parsing filesystem logs. I wanted a quick way to just insert the data so I created this script. Simply copy the ESLog.py script into your NZBGet/scripts directory. In NZBGet, select settings and set the hostname of your ElasticSearch instance. You can download the plugin on github| Chris Bergerons Tech Blog
How to improve the performance of Jaeger when using Elasticsearch as the storage backend.| karlstoney.com
Dear TheHive and Cortex users, If you are running TheHive v3.5.0 and / or Cortex v3.1.0, the underlying database is Elasticsearch v7.x. Elastic recently released two new versions: v7.11.0 and v7.11…| TheHive Project