Enterprise resource planning is one of the primary management tools used by most medium-sized companies. This so-called ERP system coordinates all company-relevant information on production processes, purchasing and sales figures, invoices or customer data.
Professional database optimization - When databases reach their performance limits
Online shopping, social networks, Big Data: The flood of data is growing - the storage capacity of current databases is slowly starting to reach its performance limits, despite modern technologies. Experts predicted the danger years ago and began searching for solutions. In the meantime, the urgency has become public, and intensive research is underway to meet the new requirements.
What do you want to do with your data? That decides on the right database solution and database optimization!
Relational database management system
In this model, the individual properties of each object are recorded and stored in part-oriented tables. In other words, the objects are entered in rows, their individual attributes in columns. As a result, things that belong together are found in the same or directly adjacent blocks and can be managed quickly and clearly using query-optimized access mechanisms and index structures. Disadvantage: The more data has to be managed, the more powerful the server has to be. But despite fast CPUs, performance eventually reaches its limits. And scale-ups for higher performance are very cost-intensive.
In addition, there are numerous other data infrastructures, whose respective advantages and disadvantages, however, are controversially discussed even in expert circles. Among them are CRM systems or archive solutions, for example. They are usually loaded with particularly large volumes of data, so-called bulk uploads, and are queried predominantly on a read-only basis. However, very complex, cross-domain queries often cause these systems difficulties when it comes to performance.
New techniques development
New databases operate under the general buzzword NoSQL. The abbreviation stands for "Not Only SQL". Here is an overview of some of the innovative developments:
- Key-value databases: store values exclusively under a single key. Pro: good scalability and performance. Example: "Riak".
- Column databases: extensive data model is based on unconnected tables. Pro: High scalability. Example: "Apache HBase".
- Document-oriented databases: flexible data model. Documents are stored as Javascript Object Notations. Thus one is able to represent also complete structures. Pro: good scalability. Example: "MongoDB".
- Graph databases: data is mapped as graphs. Pro: easy search and editing. Example: "Neo4j".
How do enterprise databases work?
Databases are primarily intended to map corporate structures. They are basically managed and maintained by database management systems.
In focus:
comprehensive functionality
Data security
New developments are making their way into the public domain to accommodate the vast digital information ranging from business intelligence to online purchases to ad hoc requests in real time. For the most part, however, people currently still rely on a traditional model: the relational database management system, which is already twenty years old.
Professional database optimization makes sense even for medium-sized companies
But here, too, the efficiency of the programs based on the databases is beginning to suffer: Increasing demands on the scope of functions, growing archives and increasing floods of data slow down workflows. Queries take more time or, in the worst case, are no longer executed correctly. The data organization must therefore also be adapted to current requirements in order to avoid confusion and expensive waiting times.
