Many companies use ElasticSearch as a search engine, to supplement their main database. Some of the well-known tech giants utilizing elastic search are ;
Netflix uses the ELK Stack to monitor and analyze customer service operations and security logs in a variety of ways. Elasticsearch, for example, is the backbone of their message system. Elasticsearch was also chosen because of its automatic sharding and replication, configurable schema, user-friendly extension approach, and a large ecosystem of plugins. Netflix has grown its Elasticsearch deployments from a few isolated deployments to over a dozen clusters with several hundred machines.
eBay has built a unique ‘Elasticsearch-as-a-Service’ platform to facilitate easy Elasticsearch cluster installation on their own OpenStack-based cloud platform, which is used for a variety of business-critical text search and analytics use cases.
Walmart uses the Elastic Stack to unlock the hidden potential of its data in order to get insights into customer purchase habits, track store performance indicators, and analyze holiday trends in near real-time. It also makes use of ELK’s security capabilities for SSO, anomaly detection alerting, and DevOps monitoring.
T-Mobile is a well-known mobile phone company. Elasticsearch powers its Android and Apple iOS mobile apps. Since T-Mobile launched its new app, which was completely redesigned from the ground up, the app’s customer ratings have surged, and the app has also become a marketing goldmine for T-Mobile.
When it comes to implementation, there are a variety of options available.
Elasticsearch can be used to search a variety of different types of data. It has a scalable search solution, near real-time search, and multi-tenancy support. Elasticsearch collects unstructured data from a variety of sources, stores, and indexes it using user-defined mapping (which can also be derived automatically from data), and makes it searchable.
Its networked architecture allows it to search and analyze massive amounts of data in real-time. It allows you to start small and build up to hundreds of machines. Running a full-featured search cluster with Elasticsearch is simple, but scaling it needs a significant amount of experience.
When working with JSON-formatted data, Elasticsearch takes a document-oriented approach. The index and type can be used to organize and store data. Multiple indices and types are possible. You can think of the index as a database and the types as tables in a conventional relational database. Here’s a quick comparison of relational databases with Elasticsearch.
Elasticsearch > Indices > Types > Documents with properties
MySQL > Databases > Tables > Columns/Rows
A search query, also known as a query, is a request for data from Elasticsearch data streams or indexes.
A query can be thought of as a question written in an Elasticsearch-friendly format. You can use a query to acquire answers to questions like these, depending on your data:
One or more queries are merged and delivered to Elasticsearch to form a search. In the hits, or search results, section of the answer, documents that match a search’s queries are returned.
Additional information may be found in a search, which can be used to improve the process. A search could, for example, be confined to a single index or only return a certain amount of results.
You may search and aggregate data stored in Elasticsearch data streams or indices using the search API. The query request body parameter of the API accepts Query DSL queries.
Using a match query, the following request searches my-index-000001. This query looks for documents with the user.id kimchy. (Elasticsearch 7.16 official example)
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Elasticsearch (also known as ES) is an Apache Lucene-based contemporary search and analytics engine. Elasticsearch is a NoSQL database that is completely open-source and written in Java. This means it stores data in an unstructured manner and cannot be queried using SQL.
Elasticsearch and its terminologies, on the other hand, are not that unlike a database, which is currently widely used in the industry. So, here’s a comparison so that you can link these Elasticsearch words to additional RDBMS terminologies:
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