There are several reasons why many organizations are turning to NoSQL databases to manage big data.
NoSQL databases are designed to scale horizontally, which means they can handle large amounts of data and a high volume of read and write operations by distributing the workload across multiple machines. This makes them well-suited for handling big data.
NoSQL databases are designed to handle a wide range of data types and do not require a fixed schema, which means they can handle data that is structured, semi-structured, or unstructured. This makes them well-suited for handling data that may be too complex or varied to be stored in a traditional relational database.
NoSQL databases are designed to offer high performance and low latency, which makes them well-suited for handling real-time big data processing and analytics tasks.
NoSQL databases often require fewer hardware and software resources than traditional relational databases, which can make them more cost-effective for handling big data.
Many NoSQL databases are designed to be used in cloud environments, which makes them well-suited for handling big data in a cloud-based architecture.
Overall, the scalability, flexibility, performance, cost-effectiveness, and cloud-friendliness of NoSQL databases make them an attractive option for organizations looking to manage and analyze large volumes of data.
More to read
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- Relational Vs Non Relational Database
- 13 Examples of Relational Database
- Relational Database Vs. Object-Oriented Database
- 9 Types of Databases
- Distributed Database
- Operational Database
- Personal Database
- Centralized Database