Converged database
A converged database is a type of database system that combines multiple data models and processing capabilities into a single platform. Unlike traditional databases that focus on a specific data model (for example, relational or NoSQL), converged databases provide a unified environment for storing and processing structured, semi-structured, and unstructured data. This approach simplifies data management, reduces data silos, and enables versatile analytics across diverse data types.
Functions of converged databases include the following:
- Unified platform: Converged databases integrate various data models, including relational, document, graph, and more, within a single platform. This allows different data structures to coexist and be queried together.
- Data flexibility: Converged databases accommodate structured, semi-structured, and unstructured data, eliminating the need to transform or preprocess data before analysis.
- Data processing: These databases offer diverse processing capabilities, enabling users to perform analytics, querying, and reporting on various data models without switching platforms.
- Unified query language: Converged databases often provide a single query language that supports all supported data models, simplifying data retrieval and analysis.
- Scalability: Many converged databases offer scalability options, allowing users to expand their data processing and storage capabilities as their needs grow.
Advantages of converged databases include the following:
- Reduced complexity: Converged databases streamline data management by providing a single platform for different data models, reducing the need for data transformation and integration
- Versatile analytics: Users can perform complex analytics and queries across different data types without the need for separate tools or systems
- Data agility: Converged databases allow organizations to adapt to changing data requirements and structures without migrating data between different systems
- Cost efficiency: By consolidating data storage and processing on a single platform, converged databases can reduce infrastructure and operational costs
- Holistic insights: Converged databases enable organizations to gain holistic insights by analyzing relationships between different data types
Use cases include the following:
- Enterprise data lakes: Converged databases are used in building enterprise data lakes, where data from various sources is ingested, stored, and analyzed in a unified environment
- Multi-model applications: Applications that require different data models, such as relational and graph, can benefit from converged databases that support both models within a single platform
- Content management: Organizations managing diverse types of content, such as images, videos, and documents, can benefit from a converged database to manage and analyze their content
Here are a couple of examples of converged databases:
- Oracle Database: Oracle offers a converged database that supports various data models, including relational, document, and graph, along with advanced analytics capabilities
- SAP HANA: SAP HANA provides a converged in-memory database platform that supports both relational and columnar storage, enabling real-time analytics on a variety of data types
Converged databases provide a unified platform for storing, managing, and analyzing various data models within a single system. Their ability to handle diverse data types and processing capabilities offers organizations greater agility, efficiency, and insights across their data landscape.