In-Memory Analytics is an emerging technology that is putting forth solutions to support Business Intelligence in making faster, smarter decisions. In-Memory processing stores all the data and calculations in RAM. By placing storage in RAM, firms can experience faster processing which allows for quicker access to data and calculations that answer BI questions. Businesses can take the answers to these BI questions and translate them into informed decisions. By bypassing slower queries, and indexes stored on hard disks, and utilizing the growing capabilities of the PC, businesses can leverage their processing power in more efficient ways . In the recent past this had not been possible as most PCs were 32-bit and could only support up to 4GB of memory. This greatly restricted the capabilities of in-memory analytics. More recently, PCs have become 64-bit and can now support up to 1TB of memory, this allows for large amounts of data to be cached in the computer’s RAM. 
According to the Gartner’s Hype Cycle for Emerging Technologies report , published in August 2013, this technology could potentially plateau in less than 2 years. On the hype cycle it is shown as currently emerging from the Trough of Disillusionment. Many of the articles I researched seemed to have been written while in-memory analytics was in the Peak of Inflated Expectations. As in-memory analytics becomes a more mature technology the expectations around it will become more realistic. This will be a positive development for the field as resources will be dedicated to real world solutions rather than the pipe dreams of the tech world.
|Image found at http://www.gartner.com/newsroom/id/2575515|
There are many companies that have started offering solutions for in-memory or flash analysis. Some of these companies include: IBM, SAS, SAP and Oracle. SAP and Oracle currently stand out as having the more robust products. SAP sells HANA (High-Performance Analytic Appliance) while Oracle markets Big Data and Exalytics. These solutions are pretty exciting and it looks like they are becoming increasingly competitive. SAP is currently winning the memory war as it reports that HANA is scalable to 16TB. I found this buyer’s guide write up by Drew Robb to be an informing read. Robb goes in depth to compare many of the most prominent in-memory analytic products in the marketplace today.  http://www.enterpriseappstoday.com/business-intelligence/in-memory-analytics-buyers-guide-oracle-big-dataexalytics-appliances-vs.-sap-hana.html
There are some caveats that we should keep in mind as we climb out of the Trough of Disillusionment. This isn’t going to be a silver bullet for all companies. In fact it is definitely safe to say that this is not for everyone. As more users seek to access large amounts of data RAM will need to be increased, and although the cost is declining it still isn’t free. Companies that need answers fast so that they can implement time critical decisions are going to be able to see a greater return than the larger, bulkier companies that have the luxury to examine their decisions with a fine toothed comb. If you are a large company that cannot immediately act on the data then you will not benefit from the time savings gained from utilizing in-memory analytics. However, if you are a firm that benefits from every second you are out ahead of your competitors then in-memory analytics should be explored and invested in.