Learn how you can use this open source search and analytics engine to enrich your applications, simplify development and management tasks, and much more.
Elasticsearch (link resides outside ibm.com) is an open source search and analytics engine based on the Apache Lucene library. Initially released in 2010 by Elastic, Elasticsearch was designed as a distributed Java solution for bringing full-text search functionality into schema-free JSON documents across multiple database types.
Elasticsearch provides extremely scalable search capabilities by taking unstructured data types from various sources and storing them in specialized formats for optimized language-based searches. Elasticsearch also features a RESTful API (link resides outside ibm.com) design that gives developers incredible flexibility when calling different data formats for visualization and analysis.
Databases for Elasticsearch
Apache Lucene (link resides outside ibm.com) is a free, open source search engine library written entirely in Java. Lucene is primarily recognized for its implementation of search engines. Several projects exist to expand its capabilities, including Elasticsearch.
Lucene utilizes documents as its main unit of search and index. Because it indexes and stores all document contents into keyword-centric data structures, Lucene can achieves extremely fast search response times. Content stored on Lucene can come from various sources including websites, filesystems, and databases like PostgreSQL.
Learn more about PostgreSQL by reading "Database Deep Dives: PostgreSQL."
Elasticsearch provides a number of benefits for developers looking to create a fast, reliable full-text search solution for their enterprise databases; but, quick search capabilities are only one of the many features that Elasticsearch has to offer (link resides outside ibm.com).
Elasticsearch makes it easy to add more capacity and reliability to your nodes and clusters. Elasticsearch scales with your enterprise and supports cross-cluster replication (CCR) on an index-by-index basis. This gives your organization the ability to utilize all of Elasticsearch’s features while reducing latencies for users and ensuring high availability of services.
As an open source solution, Elasticsearch is extremely adaptable and approachable by developers and supports multiple coding languages, including Java, Python, .NET, PHP, Plus, and more.
Another great feature of Elasticsearch is its auto-complete functionality. Its user-friendly design makes it easy for users to improve their search provision and find relevant results as they type out their queries.
One of the defining features of Elasticsearch is its compatibility with a variety of plugins and integrations. This includes API extensions, alerting tools, security plugins, data recovery integrations, and more. The easy-to-extend functionality of Elasticsearch makes it easily adaptable to all of your enterprise’s needs without sacrificing its core capabilities.
Elasticsearch's speed and flexibility make it ideal for time-sensitive use cases. With a number of built-in features, Elasticsearch can be used in a variety of ways (link resides outside ibm.com) to support both infrastructure monitoring and security analytics.
In Application Performance Management (APM), finding and properly addressing roadblocks in your code all comes down to reliable search. Elasticsearch can correlate logs and metrics to make them indexed and easily searchable across your entire infrastructure. This gives development teams the tools they need to minimize lead time in addressing critical performance issues and avoiding costly bottlenecks. And, because Elasticsearch is open source, many developers have already created useful ways to leverage Elasticsearch’s APM capabilities to the fullest extent.
Security information and event management (SIEM) is a critical component of increasing security posture in today’s digital landscape. By leveraging Elasticsearch’s speed, scale, and analytical power, security teams can automate the correlation of billions of lines of log data to look for network vulnerabilities and potential data breaches.
Elasticsearch indexing supports near real-time monitoring and its powerful search capabilities help IT administrators maintain complete transparency across an entire network to quickly uncover and address potential threats as they arise.
As your enterprise begins to scale, it may become necessary to start unifying all of your content across multiple platforms, CRM tools, and databases. Because of its ease of deployment and intuitive interface, Elasticsearch creates a sustainable solution for enterprise search capabilities across all applications and services.
Elasticsearch’s out-of-the-box relevance makes it highly polished and easy to work with, making it the perfect solution for multiple teams to use, including engineering, R&D, marketing, sales, and customer support teams.
If your organization needs the flexibility of a full-text search engine with the additional support of database backups, serverless scaling, and fully managed out-of-the-box integrations, IBM has you covered.
IBM Cloud Databases for Elasticsearch is an enterprise-ready, fully managed solution for JSON document indexing and full-text search capabilities, offering 99.95% availability, GDPR- and HIPAA compliance, and much more.
Learn more about Databases for Elasticsearch by visiting the documentation.
Looking for an Elasticsearch tutorial? Try Databases for Elasticsearch, which guides you step-by-step through creating and provisioning an IBM Cloud Databases for Elasticsearch deployment.
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