Running Big Data Jobs with Elasticsearch Data

Elasticsearch

Elasticsearch is a distributed, RESTful search and analytics engine that can be used to search all kinds of documents. It provides scalable search, has near real-time search, and supports multitenancy. Elasticsearch is popular because it's easy to use and has a lot of features. It's also open-source and has a large community of users. Elasticsearch is a NoSQL database because it doesn't use the traditional SQL relational database model. Instead, it uses a document-oriented model that allows for more flexibility and scalability.

Big Data

Big data refers to data that is so large, fast or complex that it's difficult or impossible to process using traditional methods. It can be a combination of structured, semi-structured and unstructured data collected by organizations that can be mined for information and used in machine learning projects, predictive modeling and other advanced analytics applications. Big data technology deals with data storage that has the capability to fetch, store, and manage big data. It allows users to store the data so that it is convenient to access. Big data analytics helps companies leverage their data to identify opportunities for improvement and optimization. Across different business segments, increasing efficiency leads to overall more intelligent operations, higher profits, and satisfied customers.

With the growing popularity of both Elasticsearch for data storage and big data for compute workloads, it is unsurprising that many organizations are seeking to run big data jobs with Elasticsearch data. Kaspian offers a native connector for this operation. Just register your Elasticsearch datastore and link your Big Data job; Kaspian's autoscaling compute layer makes it easy to crunch through any data in your cloud with minimal setup or management.

Learn more about Kaspian and see how our flexible compute layer for the modern data cloud is already reshaping the way companies in industries like retail, manufacturing and logistics are thinking about data engineering and analytics.