Search Engine Development
Elasticsearch is an open source search engine highly scalable. It allows you to keep and analyse a great volume of information practically in real time.
"ELK" is the acronym for three open source projects: Elasticsearch, Logstash, and Kibana all developed, managed and maintained by Elastic.
Elasticsearch is a search and analytics engine. Logstash is a server‑side data processing pipeline that ingests data from multiple sources simultaneously, transforms it, and then sends it to a "stash" like Elasticsearch. Kibana lets users visualize data with charts and graphs in Elasticsearch.
Easticsearch is very useful for big data, making it easy to analyse million of data in almost real time searches. Elasticsearch lets you understand billions of log lines easily. It provides aggregations which help you zoom out to explore trends and patterns in your data.
Elasticsearch allows you to filter search results based on different criteria, to further narrow down the results. If you add new search queries to a set of documents, it might change the order based on relevancy, but if you add the same query as a filter, the order remains unchanged.
SIXSIGMA TECHNOSOFT work with clients around the globe to provide implementation and development services for the ELK stack. Some can used Crest’s ELK apps to monitor Data Center Infrastructure (Servers, Storage, and Switching data) while others have used them to build advanced insights for security technologies in the areas of network, endpoint, access, malware, identity, and vulnerability.
Logstash can unify data from disparate sources and normalize the data into your desired destinations. It allows you to cleanse and democratize all your data for analytics and visualization of use cases.
The ELK Stack is popular because it fulfills a need in the log management and analytics space. Monitoring modern applications and the IT infrastructure they are deployed on requires a log management and analytics solution that enables engineers to overcome the challenge of monitoring what are highly distributed, dynamic and noisy environments.
Kibana, which is developed by the same company, provides a real-time summary of the data, plus several customized visualization and analytics options. Kibana is free and has detailed documentation.
Full-text searches: By ranking each document for relevance to a search by correlating search terms with document content using TF-IDF count for each document, fuzzy searches are able to rank documents by relevance to the search made.
The Elastic cluster is easily scalable and can hold large amounts of data scaling even to Petabytes. It is offered in popular languages like PHP, .NET, Python, Java etc and works well with popular web-frameworks like Laravel.
Businesses nowadays looking for alternate ways where the data stored in such a way that the retrieval is quick. This can be achieved by adopting NOSQL rather than RDBMS for storing data. Elasticsearch is one such NOSQL distributed database.
Direct, Easy and Fast access: Documents are stored in a close proximity to the corresponding metadata in the index. This reduces the no of data reads and as a result increases the search result response.
Our best in class engineering team can provide inexpensive custom development to support your Elastic Stack efforts, and we’ll apply our deep insights into retail, manufacturing, distribution, and logistics to enrich your Elastic Stack initiative.