Know Your Data in Elasticsearch
Discover, classify, and manage sensitive and personal data in Elasticsearch
How Elasticsearch and BigID Work Together
BigID automatically finds, maps, and inventories sensitive data at scale in Elasticsearch—one of the most widely used distributed systems for real-time, indexed search and analysis of unstructured data that doesn’t use native indexing.
BigID scans that data in Elasticsearch without requiring a dedicated connector—for fast, efficient, and reliable data discovery.
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Benefits of Elasticsearch
Achieve fast responses because it searches by index instead of searching the text directly.
Easily adds more capacity and reliability to nodes and clusters, increasing speed and overall performance.
Support for Multiple Languages
Adaptable and developer-friendly, supports multiple coding languages, including Java, Python, .NET, and PHP.
Quickly executes complex queries. Caches almost all commonly used structured queries as a filter for the result set, and executes them only once.
Stores real-world complex entities as structured JSON documents and indexes all fields by default for higher performance.
Records changes made in the transaction logs on multiple nodes in the cluster, minimizing the chance of data loss.
Elasticsearch is a full-text, API-driven, distributed NoSQL database. It uses documents rather than schema or tables, and allows for real-time search and analysis of the data, which is stored in JSON format. Elasticsearch offers easy and fast search result responses. It has a distributed architecture that can scale up to thousands of servers and accommodate huge amounts of data.
Elasticsearch is one of the most widely used distributed systems, benchmarking one million writes per second. Over 2,500 top companies, such as JPMorgan Chase, American Airlines, Dell, and Cisco, use Elasticsearch to find patterns and trends in their data.