Understanding In-Memory Databases for DBAs

Introduction

Disk storage is used for preserving data in a database management system (DBMS). Because the information is on the disk, the data must first be retrieved, and then modified or read on disk as well.

The in memory databases DBAs must utilize enable them to speed up accessing data. Many DBMSs handle the staging data process in memory using a buffer pool or cache. This technique bypasses the disk I/O and increases the efficiency of succeeding accesses to the same data that was put in memory.

For a long time, empowering database information for access using the in memory has proven to be reliable. Performance problems can occur though due to the back and forth movement of data. Today, there are several newer strategies that DBAs can use to accomplish in memory storage and management tasks that may help improve database performance.

The In Memory Database Management System

The in memory database management system (IMDBMS) also referred to as a main memory database system, is sometimes mistakenly thought of as a system that doesn’t use disk storage but rather uses memory for storage purposes.

Solid State Disk (SSD) in memory method

One different way to use in memory is the solid state disk (SSD) method. SSD stores persistent data by using memory chips. This is in contrast to the spinning disk. SSDs were pricey in early distribution decades ago. The price has dropped since then. SSDs present an alternative way to introduce in memory databases DBAs. Unfortunately, it may not be the wisest option out there.

Current IMDBMS solutions

Contemporary IMDBMSs give DBAs a better solution over the common DBMS using SSD storage. That’s because technology advancements enable IMDBMS to conduct operations while in memory in addition to providing storage capabilities.

For disk storage, RDBMS (relational database management system) has an inherent function for buffering data or caching it, and that worked perfectly for its intended purposes.

By contrast, IMDBMS was developed to comprehend that the in memory holds the data. All unneeded components of a typical DBMS can be removed. When this happens performance speeds up tremendously.

In memory functionality is another benefit of IMDBMS. The DBS12 for z/OS by IBM is an IMDBMS. Although DB2 isn’t an all-data-in-memory system, it does provide exciting ways to optimize data. The in memory framework, Fast Traversal Block (FTB) can work with unique indexes.

How it works is that first, traversals used regularly are indexed. DB2 detects which indexes are frequently used for traversals, and when a boundary limit is reached, DB2 automatically constructs an FTB away from the buffer pool in storage space.

Next, traversals can be performed extremely fast because the upper levels of the index are cached. In addition, DB2 brings to the table in memory possibilities for larger buffer pools and better management of them along with generous quantity insert processing.

IMDBMS offers a complete way to store all data in memory. For example, compressed formatting increases available storage space and thereby, makes it more efficient to access to data.

What’s more, a combination IMDBMS where databases have both in memory and traditional disk storage capabilities can be constructed. Improved performance and lowered costs are two advantages of that option.

Speaking of the performance advantage of IMDBMS, when compared to disk storage, in memory wins the prize in the processing category. The inner workings make a difference.

Conclusion

Technology is moving so fast that even in memory databases DBAs might question the relevancy of IMDBMSs. The reality is that IMDBMSs are the wave of the near future. A legitimate concern is the cost of implementing an IMDBMS. This makes it not feasible to transfer every piece of data there economically.

DB2 DBMSs are early adopters of a hybrid IMDBMS solution. This can be good or bad depending on how it’s perceived. The latest database offerings that feature in memory features and optimized functionality may take a backseat to a traditional and in memory combo mix.

The main take away is that DBAs should look forward to implementing in memory storage and management processes. It’s forthcoming, and the prognosis is that better productivity and bolstered up performance is on the horizon.