OpenSearch
This is a search and analytics suite designed for businesses and developers who need to ingest, search, visualize, and analyze large amounts of data. Released as a fully open source project in July 2021, it emerged out of a fork of Elasticsearch and Kibana, with the explicit aim of preserving a free, community-driven ecosystem for search, observability, and analytics operations. The suite includes a core search and analytics engine, a web-based dashboard for visualization (OpenSearch Dashboards), and a set of plugins that extend functionality for security, machine learning, and data performance.
As a platform, OpenSearch supports structured and unstructured data ingestion, offers real-time search with full-text capabilities, and scales from small setups to data-intensive enterprise use cases. Companies across various industries use OpenSearch for tasks like website search, log analytics, security event monitoring, machine learning, and infrastructure observability.
SelfHosted
It can be entirely self-hosted, meaning you can download, install, and manage the software on your own hardware, private cloud, or virtual machines. This lets you retain complete control over your data, security, and resource allocation. Self-hosting is possible on Linux, Windows, or even containers like Docker to suit different IT environments.
Users can deploy both the OpenSearch engine and OpenSearch Dashboards as self-hosted applications. For more complex architectures, OpenSearch supports distributed clusters, enabling you to scale your setup by adding more nodes as your data grows. This self-hosted option is attractive for organizations that require compliance, privacy, or have specific networking and security requirements that managed cloud solutions may not meet.
OpenSearch is also available as a managed cloud service—such as Amazon OpenSearch Service but the self-hosted, open source version remains a core offering suitable for total control and customization.
Open Source?
It is fully open source, licensed under the permissive Apache 2.0 License. This means the code base is publicly available, free to use, and can be modified, extended, or redistributed without licensing fees. The project is actively developed by the OpenSearch community, which includes businesses, individuals, and partners collaborating to drive the roadmap and new feature sets.
There are no vendor lock-ins or hidden costs, and companies of all sizes can tailor OpenSearch to their needs—whether by adding plugins, customizing dashboards, or altering core functionality for internal requirements.
Features
Real-time full-text search, log analytics, data security, customizable dashboards, anomaly detection, vector database capabilities, and integrations with popular data sources. Through its dashboards, users can visualize metrics, set alerts, and automate reporting tasks for business intelligence, infrastructure monitoring, and application performance tracking.
The platform supports analytics, allowing users to explore massive datasets, search with complex queries, and glean actionable insights. Extensible via plugins, OpenSearch helps teams add features like custom index ranking, schema management, advanced authentication, and more.
Scalability is built-in; OpenSearch clusters can span multiple nodes for high availability and performance, making it a viable choice from small single-server implementations to multi-terabyte, high-ingest enterprise environments.
Small Businesses
Small businesses benefit from adopting OpenSearch in several ways. First, as an open source and self-hostable solution, there are no licensing fees, which lowers entry costs. This makes it accessible for startups or small teams with limited budgets who still require robust search, analytics, or observability tools.
Second, OpenSearch’s modularity lets organizations start small and scale their installation as needs grow. You can run OpenSearch on modest hardware or virtual machines for smaller data volumes, then expand to additional servers as your company and data needs evolve. The platform’s documentation, community support, and straightforward deployment options, such as Docker containers, help ease adoption for organizations with limited IT resources.
Small businesses can use OpenSearch for their website search, business intelligence dashboards, log collection, error monitoring, and simple machine learning applications such as anomaly detection. The dashboard offers an intuitive interface for setting up searches and visualizations, which is valuable for teams without dedicated data engineers.
However, it is important to consider that running your own OpenSearch cluster does require some operational knowledge: tasks like security hardening, regular backups, upgrades, and performance tuning fall on your organization when self-hosted.
The Broader Open Source Ecosystem
The OpenSearch project is community-driven, with a transparent development process, active contributors, and an open governance structure. Hundreds of contributors and organizations participate in driving new features, reviewing code, documenting use cases, and providing technical support in forums and chat channels.
Since its inception, OpenSearch has grown and has been adopted by both large enterprises and small organizations for a variety of use cases web search, e-commerce, security analytics, and IT monitoring being among the most prominent.
The platform is compatible with a wide ecosystem of integrations and plugins, including those developed for Elasticsearch before the licensing bifurcation. Many of the existing connectors, libraries, and client APIs work directly with OpenSearch, making migration or extension relatively straightforward.
It very interesting tool to checkout: https://opensearch.org/