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Databricks, developed by the creators of Apache Spark, is a Web-based platform, which is also a one-stop product for all Data requirements, like Storage and Analysis. It can derive insights using SparkSQL, provide active connections to visualization tools such as Power BI, Qlikview, and Tableau, and build Predictive Models using SparkML. Databricks also can create interactive displays, text, and code tangibly. Databricks is an alternative to the MapReduce system.
Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform, making it easy for businesses to manage a colossal amount of data and carry out Machine Learning tasks.
It deciphers the complexities of processing data for data scientists and engineers, which allows them to develop ML applications using R, Scala, Python, or SQL interfaces in Apache Spark. Organizations collect large amounts of data either in data warehouses or data lakes. According to requirements, data is often moved between them at a high frequency which is complicated, expensive, and non-collaborative.
However, Databricks simplifies Big Data Analytics by incorporating a LakeHouse architecture that provides data warehousing capabilities to a data lake. As a result, it eliminates unwanted data silos created while pushing data into data lakes or multiple data warehouses. It also provides data teams with a single source of the data by leveraging LakeHouse architecture.