Scalable, secure data storage and management in the cloud for optimized performance.
The Cloud DBMS (database management system) represents the latest progression in database management. It is a powerful system designed to provide secure, scalable, and efficient data storage, retrieval, and management capabilities. By leveraging distributed computing, it ensures seamless data access and performance optimization. With its suite of tools, it also promotes consistency in data management and accelerates routine tasks.
Financial firms lose a significant amount of revenue due to fraud and theft each year. To combat this, these organizations are increasingly turning to cloud databases that can quickly detect anomalies between data and transactions at scale, allowing them to identify fraud as it occurs or even before it happens.
In order to maximize the value of their data, organizations need the ability to store, process, and analyze complex data sets in real time. Cloud databases provide the agility and responsiveness necessary to reduce costs and increase efficiency. With support for NoSQL, cloud databases are helping organizations with both analytical and operational use cases.
Many organizations are using data science and predictive analytics to gain insights from their data and improve customer experiences. However, this can only be achieved if the data stored is of high quality and various AI and ML models are built on top of it. Cloud databases are a key component of data engineering and play a crucial role in generating value for organizations.
Recommendation engines are widely used by organizations to provide personalized suggestions to customers and internal users. These engines use historical data to understand what people have used in the past and predict the selections users might make in the future.
When building web and mobile apps, companies often have to deal with different data structures for different data sources. Cloud databases provide high flexibility and scalability for these scenarios, allowing developers to focus on building better customer experiences instead of optimizing the database.
Here is a comprehensive Cloud Database Management Systems (DBMS) requirements checklist you can use to further define your use case.
Must help database administrators effectively manage and monitor the transactions in the database and alert the users of any problems.
Must adhere to established security standards to ensure data protection.
Must provide the ability for the database to adjust to demand by adding or removing resources, or altering the amount of data, volume of requests, and size of requests.
Must have access control for different groups based on roles within the organization.
Must support different deployment models as well as eliminate the need to purchase hardware and set up a network.
Must have features that allow users to have quick access to cloud databases remotely through the provider's API or web interface.
Must secure data whether it is stored or in transmission.
Must perform analytics and generate insights from the data available in the database.
Must integrate with analytics, metadata management tools or data integration tools so users can analyze the data, send the data to different systems and manage the metadata.
Must support identity management features for strong and adaptive authentication, privacy management, cross-protocol, SSO, and more.
Must optimize query performance for faster results with less resource consumption and fewer failures.
Must provide security at the network level to control access to database servers.
Must support different types of databases to accommodate non-relational types of data.
Must support loading or extracting different types of data with scalability and performance.
Here are some of the more popular Cloud Database Management Systems (DBMS) products.
MariaDB is a versatile fork of MySQL, supporting transactional, analytical, and hybrid workloads.
MongoDB Atlas is a document-based database with a unified interface for CRUD operations.
Redis is an in-memory database specialized for real-time and transactional use cases.
Supabase is a PostgreSQL relational database with real-time REST API and serverless functions.
FaunaDB is a NoSQL database that combines the best of relational and NoSQL architectures.
Oracle offers autonomous databases with advanced tuning and management.
Cloudera provides services for organizing, analyzing, and centralizing data.
Couchbase Capella is a multi-modal NoSQL database focusing on non-relational databases.
Azure offers managed services with integrated data management and security.
CockroachDB is a cloud-native, distributed SQL database with auto-sharding for handling unpredictability.
Teradata specializes in data warehousing and analytical use cases with advanced analytics.
Snowflake supports analytics, data lakes, and data warehouses with automated management features.
Google offers serverless database services for flexible resource usage.
Databricks provides an open-source lakehouse storage and SQL capabilities for data lakes.
PlanetScale offers a MySQL-compatible, serverless database with customizable features.
MarkLogic is a NoSQL database for transactional use cases.
AWS provides diverse cloud services suitable for various data workloads.
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