You are probably not using the right database for your time-series data.

Would you pour battery acid into a champagne glass? Of course not. A champagne glass, after all, is not designed for battery acid. When it comes to databases, however, most companies are unaware that when they input time-series data into an ordinary database, they are "pouring acid into a champagne glass."

An ordinary database is fine for ordinary data. Standard databases are usually "relational" in nature, maintaining a set of separate, related files that combine to provide information when required. In order to accommodate the unique requirements of time-series data, many relational database vendors provide "quick fixes" to work around problems. However, as the sheer volume of time-series data that organizations are required to manage expands, the "quick fix" becomes increasingly inadequate.

What are the unique requirements of time-series data that make standard relational databases insufficient? First, time-series data is usually collected in massive quantities. Because relational databases are not designed for time-series data, they require tons of space to organize and store it. This means more money has to be spent on disk space. Additionally, every company utilizing a relational database for time-series data collection eventually - usually sooner rather than later - runs out of space.

Second, the data is often input at an extremely rapid pace (sometimes in less-than-one-second intervals). Relational databases are not equipped for this kind of input frequency, especially when coupled with the massive amounts of data often involved in time-series collection. This results in clogs and jams.

Finally, collected time-series data must be quickly retrievable to be of value. The same problems encountered while inputting time-series data reappear during the retrieval process.

The right database for your time-series data.

The technology for measuring and capturing time-series data is increasing rapidly. As the volume and speed at which data is gathered grows, so does a company's need for a database that can match the technology. Time-series data requires a database specifically designed to meet its needs.

Historis is the premier time-series database.

Historis, one of the fastest time-series databases in the world, is designed specifically to meet the intense demands of time-series data. With virtually unlimited capacity, it can handle ANY size or speed of data collection. When other databases get clogged, Historis keeps on publishing without missing a single beat.

Additionally, the design of Historis allows for natural compression of data, thus reducing required disk space. The bottom line: Historis users don't have to spend anywhere near as much money for data storage.

Historis also provides several tools for analysis as well as links to popular analytical tools S-PLUS and MATLAB and integrates easily with existing systems.

Cost Savings | Speed | Capacity | Analytics | Integration | Technology | Total Solutions