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Beyond Relational: Data storage for modern applications - Mike Lehan
Explore the limitations of relational databases and discover new data storage solutions including serverless, graph, ledger, queuing, time-series, and document databases tailored for modern applications demanding flexibility and scalability.
- Flexibility of storage is required by modern applications, as data growth affects the scope of entities and scalability of systems.
- Relational databases can be limiting, and considering data storage beyond relational databases can provide a better fit for modern applications.
- Fuzzy search and high-confident search are important features for databases.
- Serverless databases, like Atlas, can provide scalability and flexibility for modern applications.
- Time-based data storage is useful for monitoring system performance and providing real-time updates.
- Graph databases are useful for storing and analyzing complex relationships between data.
- Ledger databases, like Quantum Ledger, provide transactional integrity and auditing capabilities.
- Queuing systems, like RabbitMQ, can help manage data processing and worker load.
- Data loading tools, like Snowpipe, can assist in moving data between platforms and simplifying data processing.
- Time-series databases, like InfluxDB, are single-purpose databases designed for storing time-series data.
- Document stores, like MongoDB, provide flexible data storage and querying capabilities.