#Lakehouse com indiana update
With the upcoming release of MongoDB 6.0, users will get an update to the time-series collection, which is designed to simplify handling IoT and financial type data. The company offers a connector for the Apache Kafka pub/sub framework to streamline these types of deployments. MongoDB is also positioning its database as a good repository in which to store sensor data, event data, and streaming data from IoT devices and applications. MongoDB says developers can leverage real-time analytics to power things like personalization, fraud prevention, performance optimization, and preemptive maintenance. The New York-based company is advocating the benefits of real-time analytics in its database. MongoDB is also giving Atlas users the capability to query data across Atlas cluster and cloud object stores using SQL, without needing to flatten the data or manipulate it in any way. MongoDB 6.0 will bring a column store index among other analytic enhancements (Image courtesy MongoDB)Ītlas also gets a new SQL Interface that will give analysts a familiar way to interact with read-only data using SQL or BI tools that speak SQL. The company says it will provide “the economics” of cloud object storage in a database environment that sits adjacent to the company’s primary MongoDB store. MongoDB also announced a preview of Atlas Data Lake, which will provide an isolated “companion” data lake on which to perform analytics. This allows users to scale and tune their analytical workloads separately from the nodes used for transactional and analytical use cases, the company says. The company also announced the capability to scale analytic nodes separately from other nodes in a MongoDB cluster. Most SQL-based analytic databases store data in columns (as opposed to rows), which results in faster processing for data aggregation. The first is a column store index, which will let customers run common analytical queries without moving the data or changing its structure, the company says. To that end, MongoDB unveiled three major new features at MongoDB World this week. Delivering some analytics within the database makes sense, as it eliminates the need for companies to ETL the data into a dedicated OLAP environment, which brings latency, complexity, and cost to the equation. As a document store with a JSON-like data structure, the database was intended to make it easy for developers to build Web and mobile apps, which typically fall into the operational and transactional buckets.īut data analytics is increasingly a priority for companies, and so MongoDB is looking to build more analytic capabilities into its database. MongoDB, of course, was not designed for analytics. Some of the most compelling enhancements unveiled at MongoDB World revolve around new analytics capabilities in the upcoming version 6.0 release of the NoSQL database. MongoDB held its annual user conference this week, which means database customers have been inundated with new features and capabilities.