To survive in today's ultra-competitive business environment, companies have to be adaptable and be able to move quickly with the ever-changing market conditions. It's not enough to simply have a good strategic direction and a smart marketing plan. A business needs to be incredibly agile and able to identify new trends and potential problem areas quickly. Quick responses to changing market opportunities can generate incredible profits, and avoiding manufacturing or operation pitfalls can help save the bottom line.
In years past, generating information was a slow-paced, multi-step process. Business transactions were processed and then posted to a central system, and after that, a report with a single view of the data was generated. In today's world, there is a tremendous need for data architectures that support time-based insights and instantaneous analysis of information. With real-time analytics, data processing is revolutionized as data can be used and instantly analyzed as soon as it is generated. Rapid advances in technology are re-writing the world we live in, even in traditional sectors like farming.
The Promise of Real-Time Data Analytics
With real-time analytics, companies can enhance the experiences of their customers by quickly responding to client preferences and identified needs. High-speed analysis of just-generated information can help businesses swiftly hone in on key trends and emerging patterns of behavior. In essence, real-time analytics provides an instant window into the soul of the company.
This tool has the power to transform business. Other key advances in technology are also leading to new models for health care. By using wearable sensors and Artificial Intelligence, medical caregivers are revolutionizing the monitoring and tracking of Parkinson's in patients. Artificial Intelligence (AI) promises to transform the very world we live in. AI can already create jokes that are funnier than human-generated comedy.
In-Memory vs. Traditional Database
With an IMDB (in-memory database), the data is held within the main memory instead of having to be stored on one of the hard drives. There is no hard disk involved to slow the process down. As a result, whenever you update the data or want to query the database, speeds are dramatically faster.
An in-memory database that is designed for data analytics will offer lightning-fast access speed for tasks like Business Intelligence and real-time analysis of IoT (Internet of Things) sensor information. A further boost in performance can come when you also use an in-memory relational database management system. The fastest in-memory database can revolutionize data processing and analytics.
How an In-Memory Database Can Help Optimize Data Processing
In addition to the performance speed inherent in a memory-resident database, an IMDB offers other key plusses. The optimization algorithms with in-memory databases are much simpler and require fewer CPU instructions.
When the data for an IMDB is loaded, it is in a compressed format. This helps streamline query processing work. Multiple data transfers from disks are also eliminated, as are multiple data copies in memory, and CPU demands are minimized.
The Advantages of Using an In-Memory Database
When you use a database that is resident in memory, rather than relying on slower disk storage, you get the benefit of speed that is unparalleled. Unlike a traditional database, there is no need to constantly read and write from disk to process every single bit of data. Queries and analyses that utilize an in-memory database (IMDB) are simply lightning-fast.
An IMDB can also offer nearly unlimited scalability. With horizontal scaling, the in-memory database can be distributed across multiple systems to accommodate growth needs fully. In addition, you can augment capacity by utilizing cloud environments and moving seldom queried data off to traditional storage. With their improved performance, IMDBs can leverage improved performance to reduce a company's infrastructure and computing costs dramatically.
Ways IMDBs Help Protect Data Safety
Typically, the main memory of a system is used to support short-term data processing. Data is then secured by writing it to a hard drive. With in-memory databases, different techniques are used to help assure data continuity and integrity.
Snapshot files and transaction logs can be used to help ensure that a database can be rolled back to an earlier version. High-availability strategies can include replicating the data across different geographical areas and automatic failover protection.
The fastest in-memory database offers companies unparalleled benefits when it comes to performance, speed, and data processing efficiency. They are ideal for optimizing and supporting Business Intelligence and advanced data analytics.
