With the introduction of digital media into our daily lives, we are generating incredible amounts of data without realizing it. There is an incredible amount of data on the internet. Websites continue to generate new data every second. All such big data is called Big Data in IT language. However, most of this data generated on the internet is meaningless, scattered and unstructured. It is very important for businesses to make sense of these scattered data as a whole. Thanks to this organized data, businesses can identify problems early, create marketing strategies more easily, and get to know their customers much better in the light of this data when it comes to serving them. The majority of tools written for searching the internet are helpless in the face of disorganized and unprocessed data collections. ElasticSearch was developed for the IT world in order to overcome exactly this helplessness. So we can actually call ElasticSearch a search tool.
The ElasticSearch search tool is built on the Apache Lucene infrastructure, using the Java programming language. It is a full text, search engine and analysis tool. Lucene was developed to search text files on a single device. ElasticSearch, which was developed because of the inadequacy of businesses in searches on distributed systems and instant data, has gained popularity all over the world with its flexible structure while providing convenience to companies and its success on real-time data in distributed systems.
When registering data to ElasticSearch, the fields you previously specified in the data are indexed. Since ElasticSearch classifies the data according to the index list and performs this process easily at the first moment of data recording, users can reach search results much faster.
What ElasticSearch Gains Us
- Backup can be done much more easily than in the past.
- It is almost real-time. Thanks to this feature, you can find previously saved data seconds later in searches within the vehicle.
- It works with RestfulAPI support.
- It has a structure called Open Source.
- It works almost seamlessly in highly scalable and distributed structures.
- It is very efficient compared to alternative tools on the market and provides this efficiency by using much less resources.
- Its indexing capability is quite advanced. Thanks to Elasticsearch, it is possible to get search results very quickly.
- Cluster is quite simple in terms of structure compared to its counterparts.
- ElasticSearch supports various programming languages as it indexes files in JSON structure.
- It can perform the mapping process according to the data type.
- It has a very easy and fast installation compared to other equivalents.
- It has the ability to complete operations automatically.
- It has the possibility to transfer data directly to ElasticSearch from databases such as MongoDB, Cassandra, NoSQL and HBase, which are widely used in the IT industry.
- There are Replica and Shared concepts in the tool.
- ElasticSearch has a mapping system on itself. This concept is called the process of defining the way a document is passed to the search engine.
- The system offers high availability feature to its users.
ElasticSearch has a very simple cluster structure. In this way, you can scale the system by adding new machines to the environment without any problems when the datasets are recorded and the traffic level increases. There are nodes in the cluster and ES is run on each node. The advantages of this highly efficient cluster structure are as follows:
- Presenting the concepts of Replica and Shared to us, the users,
- Bringing the mapping system into our lives,
- Indexing of documents is done in JSON,
- Presenting the concept of index and document,
- Indexing logic,
- High availability system.
3 Benefits of Using ElasticSearch
Real Time Near Real-time Processing Capability
ElasticSearch is a very efficient tool for the industry. For the tool we are talking about, operations such as writing or reading data are generally completed in much less than a second. This feature is very important for those who use it. Thanks to these efficient actions, it is possible to utilize ElasticSearch for real-time purposes such as anomaly detection and application monitoring.
Free Add-ons and Tools
You can easily integrate ElasticSearch with Kibana, a very popular reporting and visualization tool that is very successful today. Apart from this tool, you can easily transform data with Logstash and Beats integrations and upload it to your ElasticSearch cluster. As you can see from these tools, you can also use many ElasticSearch plugins for free to add rich functionality.
Time Saving
ElasticSearch software provides us with REST-based API services, schema-free JSON documents and a simple http interface, so you can use the service at very high speeds. In addition to these features, it also allows you to write applications suitable for different uses. Despite ElasticSearch’s distributed infrastructure, it processes large amounts of data in parallel, allowing you to find results for your queries very quickly. Finally, ElasticSearch offers multi-language support to its users. The most popular programming languages are Ruby, Python, PHP, Node.js and JavaScript.
