Elastic Search: A growing ecosystem of components that are specifically designed for your growth.Learn More →
If you ask “What is Elastic Search? To ten different people, you will never get the same answer. Some may say that it is a form of index, while others may reply that it is an analytics database. You may even get answers that go along the line of “it is a big data solution”, or “a search engine”. Depending on the familiarity with the technology and how one has used it to meet their goals, these answers will bring you closer to the epiphanic realisation that they are all right.
Part of the appeal of Elastic Search lies in the extensive ecosystem of components that is now called the “elastic stack”. It is an open-source search and analytics engine that is built on Apache Lucene and developed systematically in Java. What started as a scalable version of the Lucene, in no time developed the ability to horizontally scale Lucene indices.
Why Elastic Search is The Best For Backend Development?
ElasticSearch allows developers to perform extremely fast. It attends to all the queries for the result set, so for every search query that has a cached filter, the search filter will curate from the cache. Compared to other programming languages, ElasticSearch can retrieve data in less than ten seconds.
ElasticSearch can easily be scaled up to multiple servers based on a distributed architecture. Additionally, it can store thousands of gigabytes of data. It is built in a specific way to run smoothly on any system or in any cluster with a number of nodes. When you grow from a small cluster to a considerably big cluster with countless nodes, the process becomes automatic. However, it requires a bit of planning.
A Segregated Architecture:
ElasticSearch is perfect for handling search queries. The distributed approach generally divides the indices into small sections making the matter of creating innumerable replicas easier. When new documents are added, routing and rebalancing operations have to be conducted automatically.
ElasticSearch is schema-free. Generally, it translates to the fact that it does not require any data definition. However, it uses some defaults to index the date unless you specify the data type. Moreover, it accepts JSON documents and finds the data type, indexes the records and easily makes it searchable.
When You Hire Us, You Obtain Our:
Ability to Use Every Feature that Comes With It:
In addition to its speed, scalability, and resilient nature, Elastic Search has much to offer. It comes with a number of powerful built-in features that makes storing as well as searching data efficient. However, to utilise it perfectly, one has to know about it all. Our developers have years of knowledge and experience when it comes to working with ElasticSearch. From data rollups to managing index lifestyle, our developers know it all.
Ability to Simplify The Data:
The integration with Beats and Logtash makes data procession seamless. Moreover, Kiana provides real-time visualisation of the data as well which allows quick accession of the APM or application performance monitoring, metric data, and logs.
Grow Your Business With Us
As Elastic Search uses a structure based on documents and has extensive REST APIs for storing as well as searching an extensive amount of data, you can rely on us as we can assist you in creating a well-structured database that supports your digital products. Elastic Search is based on the Lucene library that allows effortless search implementation on your website.
We are a Bangalore based Product Development and UX firm specialising in Digital Services for the whole spectrum, from startups to fortune-500s. We do not redefine anything or reinvent the wheel.