Table of Contents
- What is an In-Memory Database System?
- On-Disk Database Vs. In-Memory Databases
- How is data accessed and changed in an In-Memory Database Management System?
- How is In-Memory data shared among multiple tasks?
- Can an On-Disk database be used In-Memory?
- What are the advantages and disadvantages of In-Memory Databases?
- What is the difference between an In-Memory Database and simply storing data in shared memory segments?
- An In-Memory database can be subject of data loss if something stops working: how do you cope with this?
- Are all embedded databases also In-memory databases?
- How does Raima implement an In-Memory database system in RDM?
- All data is stored on disk, disk I/O needed to move data into main memory when needed.
- Data is always persisted to disk.
- Traditional data structures like B-Trees designed to store tables and indices efficiently on disk.
- Support a very broad set of workloads, for example, OLTP, data warehousing, mixed workloads etc.
- All data stored in main memory, no need to perform disk I/O to query or update data.
- Data is persistent or volatile depending on the in-memory database product.
- Specialized data structures and index structures assume data is always in main memory.
- Optimized for high-performance.