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What is Cloudera Operational Database (COD)? Operational Database is a relational and non-relationaldatabase built on Apache HBase and is designed to support OLTP applications, which use big data. The operational database in Cloudera Data Platform has the following components: .
When connecting, data virtualization loads metadata (details of the source data) and physical views if available. It maps metadata and semantically similar data assets from different autonomous databases to a common virtual data model or schema of the abstraction layer. The essential components of the virtual layer are.
Data Catalog An organized inventory of data assets relying on metadata to help with data management. MapReduce MapReduce is a component of the Hadoop framework that’s used to access big data stored within the Hadoop File System Metadata A set of data that describes and gives information about other data.
NameNode is often given a large space to contain metadata for large-scale files. The metadata should come from a single file for optimal space use and economic benefit. The following are the steps to follow in a NameNode recovery process: Launch a new NameNode using the FsImage (the file system metadata replica).
You can also access data through non-relationaldatabases such as Apache Cassandra, Apache HBase, Apache Hive, and others like the Hadoop Distributed File System. DataHub Source: Github DataHub is a modern data stack's open-source metadata platform of the third generation.
Relational vs non-relationaldatabases As we mentioned above, relational or SQL databases are designed for structured or tabular data. Non-relationaldatabases , on the other hand, work for data forms and structures other than tables. and its value (male, red, $100, etc.).
Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relationaldatabases. Key-value stores, columnar stores, graph-based databases, and wide-column stores are common classifications for NoSQL databases.
Oracle Data Integrator has the functionality that automatically analyzes metadata from various data stores, detects patterns, generates, and then applies data quality rules to identify any issues among actual values. The prevailing part of users claim that it is quite easy to configure and manage data flows with Oracle’s graphical tools.
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