Search Results for "elasticsearch"
Sort By:
Showing 121 open source projects for "elasticsearch"
View related business solutions-
$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
-
Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
-
1
Elasticsearch
A Distributed RESTful Search Engine
Elasticsearch is a distributed, RESTful search and analytics engine that lets you store, search and analyze with ease at scale. It lets you perform and combine many types of searches; it scales seamlessly, and offers answers incredibly fast with search results you can rank based on a variety of factors. Elasticsearch can be used for a wide variety of use cases, from maps and metrics to site search and workplace search, and with all data types. -
2
Elasticsearch Exporter
Elasticsearch stats exporter for Prometheus
Prometheus exporter for various metrics about Elasticsearch, written in Go. The exporter fetches information from an Elasticsearch cluster on every scrape, therefore having a too short scrape interval can impose load on ES master nodes, particularly if you run with --es.all and --es.indices. We suggest you measure how long fetching /_nodes/stats and /_all/_stats takes for your ES cluster to determine whether your scraping interval is too short. -
3
Laravel Elasticsearch
An easy way to use the official Elastic Search client in your Laravel
An easy way to use the official Elastic Search client in your Laravel or Lumen applications. -
4
go-elasticsearch
The Go client for Elasticsearch
Language clients are forward compatible; meaning that clients support communicating with greater or equal minor versions of Elasticsearch. Elasticsearch language clients are only backwards compatible with default distributions and without guarantees made. When using Go modules, include the version in the import path, and specify either an explicit version or a branch. The elasticsearch package ties together two separate packages for calling the Elasticsearch APIs and transferring data over HTTP, esapi and elastictransport, respectively. ... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
-
5
Elasticsearch MCP Server
A Model Context Protocol (MCP) server implementation
This MCP server implementation provides interaction capabilities with Elasticsearch and OpenSearch, enabling functionalities such as document searching, index analysis, and cluster management through a set of tools. -
6
elasticsearch-learning-to-rank
Plugin to integrate Learning to Rank
The Elasticsearch Learning to Rank plugin uses machine learning to improve search relevance ranking. It's powering search at places like Wikimedia Foundation and Snagajob. -
7
Elasticsearch Node.js client
Elasticsearch client library for Node.js
Node.js client for Elasticsearch. The client versioning follows the Elastic Stack versioning, this means that major, minor, and patch releases are done following a precise schedule that often does not coincide with the Node.js release times. Language clients are forward compatible; meaning that clients support communicating with greater or equal minor versions of Elasticsearch. -
8
Laravel Scout Elasticsearch
Search among multiple models with ElasticSearch and Laravel Scout
The package provides the perfect starting point to integrate ElasticSearch into your Laravel application. It is carefully crafted to simplify the usage of ElasticSearch within the Laravel Framework. It’s built on top of the latest release of Laravel Scout, the official Laravel search package. Using this package, you are free to take advantage of all of Laravel Scout’s great features, and at the same time leverage the complete set of ElasticSearch’s search experience. -
9
elasticsearc-php
PHP low-level client for Elasticsearch
Introducing Elasticsearch DSL library to provide objective query builder for Elasticsearch bundle and elasticsearch-php client. You can easily build any Elasticsearch query and transform it to an array. This agnostic package is a lightweight wrapper on top of the Elasticsearch PHP client. Its main goal is to allow for easier structuring of queries and indices in your application. -
Secure File Transfer for Windows with Cerberus by RedwoodCerberus supports unlimited users and connections on a single IP, with built-in encryption, 2FA, and a browser-based web client — all deployable in under 15 minutes with a 25-day free trial.
-
10
ZomboDB
Making Postgres and Elasticsearch work together like it's 2023
ZomboDB is a PostgreSQL extension that integrates Elasticsearch directly into Postgres, allowing for powerful full-text search and analytics capabilities. It manages Elasticsearch indices transparently, ensuring transactional consistency and enabling complex queries through SQL. -
11
Elastica
Elastica is a PHP client for elasticsearch
Elastica is a PHP client for Elasticsearch, providing a rich object-oriented API to interact with and query Elasticsearch indexes. It simplifies the process of building, updating, and querying search indexes, making Elasticsearch integration more accessible to PHP developers. Elastica is suitable for applications requiring full-text search, analytics, and real-time data exploration. -
12
Elastiknn
Elasticsearch plugin for nearest neighbor search
Elasticsearch is a ubiquitous search solution, but its support for vectors is limited. This plugin fills the gap by bringing efficient exact and approximate vector search to Elasticsearch. This enables users to combine traditional queries (e.g., “some product”) with vector search queries (e.g., an image (vector) of a product) for an enhanced search experience. -
13
OpenObserve
Elasticsearch/Splunk/Datadog alternative for (logs, metrics, traces)
...You can reduce your log storage costs by ~140x compared to Elasticsearch by using OpenObserve. Below are the results when we pushed logs from our production Kubernetes cluster to Elasticsearch and OpenObserve using fluent bit. OpenObserve stored data in Amazon s3 and Elasticsearch stored data on Amazon EBS volumes. -
14
Elastic Cloud on Kubernetes (ECK)
Elastic Cloud on Kubernetes
Elastic Cloud on Kubernetes automates the deployment, provisioning, management, and orchestration of Elasticsearch, Kibana, APM Server, Enterprise Search, Beats, Elastic Agent, and Elastic Maps Server on Kubernetes based on the operator pattern. -
15
Searchkit
React + Vue Search UI for Elasticsearch & Opensearch
Searchkit is an open-source library that simplifies the integration of Elasticsearch into React applications, providing tools to build user-friendly search experiences with minimal effort. -
16
ParadeDB
ParadeDB is a modern Elasticsearch alternative built on Postgres
ParadeDB is an open-source search and analytics engine built on top of PostgreSQL. It serves as a modern alternative to Elasticsearch, offering real-time search capabilities for update-heavy workloads. By leveraging PostgreSQL's robustness, ParadeDB provides a scalable and efficient solution for full-text search and analytics. -
17
dejavu
The missing web UI for Elasticsearch
dejavu is the missing web UI for Elasticsearch. Existing web UIs leave much to be desired or are built with server-side page rendering techniques that make it less responsive and bulkier to run (I am looking at you, Kibana). We started building dejavu with the goal of creating a modern Web UI (no page reloads, infinite scroll, filtered views, realtime updates, search UI builder) for Elasticsearch with 100% client-side rendering so one can easily run it as a hosted app on github pages, as a chrome extension or as a docker image. ... -
18
Docker-ELK
The Elastic stack (ELK) powered by Docker and Compose
A turnkey Docker Compose stack to spin up the ELK stack (Elasticsearch, Logstash, Kibana) for log collection, analysis, and visualization. Based on official Elastic images and enhanced with configuration defaults optimized for local development and testing. -
19
Anna’s Archive
Comprehensive search engine for books, papers, comics, magazines
...The project includes all the infrastructure required to run a full instance locally or in production, combining web servers, databases, and search indexing systems into a scalable architecture. It relies heavily on technologies such as Elasticsearch for search functionality and MariaDB for structured data storage, enabling fast and efficient querying across massive datasets. The system is designed with redundancy and replication in mind, allowing distributed deployments and mirrored environments to handle high traffic and large data volumes. It also includes tooling for importing datasets, managing metadata, and maintaining structured archives using custom formats. -
20
Canal
MySQL binlog
Canal is an open-source project developed by Alibaba that simulates MySQL slave functionality to parse MySQL binlog files. It enables real-time data synchronization and change data capture (CDC) between MySQL and other systems such as Elasticsearch, Kafka, or HBase. Canal is widely used for data integration, replication, and monitoring across distributed systems, offering high performance and low-latency log parsing. -
21
Scio
A Scala API for Apache Beam and Google Cloud Dataflow
Scio is a Scala API developed by Spotify that builds on Apache Beam to enable expressive batch and streaming data pipelines, optimized for running on Google Cloud Dataflow. Inspired by Spark and Scalding, it provides scalable, type‑safe, and production-grade data processing, with built-in support for BigQuery, Pub/Sub, Cassandra, Elasticsearch, Redis, TensorFlow IO, and more. -
22
Kibana
Your window into the Elastic Stack
Kibana is a analytics and search dashboard for Elasticsearch that allows you to visualize Elasticsearch data and efficiently navigate the Elastic Stack. With Kibana you can visualize and shape your data simply and intuitively, share visualizations for greater collaboration, organize dashboards and visualizations, and so much more. -
23
DB-TUTORIAL
Mainstream database knowledge that backend programmers should master
...Relational database sections cover SQL fundamentals and systems including MySQL, PostgreSQL, H2, and SQLite. Additional chapters examine MongoDB, Redis, HBase, Elasticsearch, and the wider Elastic stack. The repository also discusses middleware such as ShardingSphere and Flyway. Detailed indexes, operational guides, interview reviews, recommended books, papers, courses, and online ebook pages make it useful for both structured study and reference. -
24
diskover-community
Open source file indexing & storage analytics powered by Elasticsearch
Diskover Community Edition is an open source file system indexing and storage analytics platform designed to help organizations understand and manage large volumes of file data. It crawls file systems and indexes metadata using Elasticsearch, enabling fast search, analysis, and organization of files stored across different storage systems. It allows administrators and users to explore file structures, monitor storage usage, and gain insights into how data is distributed across infrastructure. By indexing file metadata from sources such as local file systems, network shares like NFS and SMB, and cloud storage, the tool provides a centralized way to analyze heterogeneous storage environments. ... -
25
Searchkick
Intelligent search made easy
Searchkick brings powerful, production-ready search to Rails by mapping Active Record models into Elasticsearch with sensible defaults and easy customization. It supports language analyzers, stemming, synonyms, misspelling tolerance, and highlighting so search results feel natural to end users. Indexing is model-centric: you declare what fields to index, add computed fields, and trigger reindexing via callbacks or background jobs, with options for zero-downtime rolling reindexes. ...