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Elasticsearch Use Cases
Log and Analyze Data
The Elasticsearch ecosystem simplifies logging and log analysis. Access data wherever it lives and index it using Beats, Logstash and Ingest Nodes.
Then create rich dashboards and analysis using Kibana®, and use Curator to put the retention period on autopilot.
Scrape and Combine Data
The Elastic Stack makes it easy to collect and index remote data. The lack of a strict schema means you can consume multiple sources of data and still keep it manageable and searchable.
Powerful full-text search capabilities enable you to move beyond conventional enterprise and ecommerce implementations to more innovative applications such as fraud detection and collaboration.
Elasticsearch has its own query DSL and built-in capabilities for autocompletion, “Did you mean” responses and more.
Event Data and Metrics
Elasticsearch can handle large amounts of time series data, such as application events and metrics. Elasticsearch components support a broad range of technologies. In the rare case that it doesn’t readily support something you use, we can extend its capabilities for you.
Use the Kibana plugin to help visualize your Elasticsearch data. Kibana includes extensive charting options, a tile service for geo data and Timelion for visualizing time series data. Boost your visualizations by attaching Elasticsearch to another database, such as MongoDB®.
We’ll help protect your data using cluster and hardware redundancy, container-based isolation, ACLs/IP whitelisting, SSL encryption, user-based authentication and optional encryption at rest.
Elasticsearch dashboard plugins come preinstalled with every cluster, along with hosted Kibana for data visualization. Use our data connectors to easily pipe data from MongoDB or Twitter™ into Elasticsearch for analysis in Kibana.
Easily add data nodes and scale clusters — without downtime. Our dedicated support team is always available to help you migrate data and scale to a larger plan size.