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TempusDB

Due to the rapidly increasing number of sensors in different sectors, in today’s infrastructures, huge amounts of event data accumulate within a very short time. Often it is not clear which exact data is available, were it can be found, how it can be provided, and which data can contribute to the insights required. Not only analyzing, but also merely storing these amounts of data represent a big challenge for today’s systems. Although online procedures allow an efficient analysis of event data, it is often necessary to store the data the analysis is based on.

TempusDB, a high-performance database for chronological data developed by us, can represent significant added value for your business. Read the information below to find out about the advantages of TempusDB in the application fields of sensor- and device data, edge- and device analytics, data feeds with a timestamp, metrics and log analytics.

 

Sensor- and device data in TempusDB
In times of digitalization, the number of data sources in businesses is constantly rising. Sensors and machines are constantly producing data in huge quantities and with a high speed. This requires a specialized database technology that can store and read sensor- and machine data very fast. The high quantities of data that accumulate in the IoT environment reveal the limits of today’s systems, which can only handle the high requirements with the help of expensive and excessive distribution.
TempusDB is the ideal solution for storing sensor- and machine data in the IoT environment. Due to the optimization to event data, it is possible to store millions of events per second – even on standard hardware and on one single node. Due to the usage of revolutionary indexing procedures, TempusDB allows the best query- and analysis performance possible. In the process, TempusDB has a high reliability and high performance recovery mechanisms in order to ensure constant availability. An intelligent distribution and loss-free data compression guarantee an ideal exploitation of your resources.

Why you should rely on TempusDB as solution for sensor- and device data
TempusDB is a high-performance event database to be applied in the IoT environment that offers a unique performance and at the same time is both resource-efficient and high-available. The linear scalability of TempusDB guarantees you a flexible adaption to your individual needs at any time. In addition, TempusDB provides the possibility to integrate your applications directly.

 

Edge-device analyses with TempusDB
Data at the network edge also needs to be analyzed.
How do you gain important insights exactly when and where you need them?
And how do you avoid a stream of unimportant data? Traditionally, data is analyzed in the core of the network. However, with the growing popularity of IoT sensors and -devices, data has to be analyzed closer to its source and to be condensed for core analysis. Edge analyses provide a better user experience and shorter response times, e.g. on cruise ships, in monitoring health statuses or full system capacities.
Edge device analyses need to take place in a fast and reliable way and with a minimal employment of resources. Thus, you need a database that is failure-resistant and can easily be applied to the right extent. TempusDB is a high-performance, highly failure-resistant NoSQL database, which has been optimized for the real-time analysis of time series data. In case of rising demand, the capacity can easily be extended with standard hardware. Even in the case of a hardware- or network failure, it can react to read- and write-queries. TempusDB requires less hardware resources with the same computing capacity so that the system is ideal for edge analyses. With TempusDB, analyses can easily be conducted with the help of SQL range queries.

Why clients use TempusDB for their edge device analyses
Whenever customer experience and real-time analyses have to be available immediately, edge analyses allow a faster reaction and fulfillment of business requirements. TempusDB is ideal for conducting edge device analyses, e.g. in monitoring error logging, tracking kiosk usage or checking prescriptions.
Telephone- and service companies quickly provide new services. They use TempusDB for the real-time analyses of their system performance because of its speed and reliability.
Software- and technology companies depend on real-time logging and -warning to fulfill customer expectations. They use TempusDB for fast storing and analysis of device- and system logs at the network edge, and aggregate this data over time.
Healthcare providers need fast performance and reliability in order to guarantee their patients’ health. They rely on TempusDB, ensuring that patient data and the data of the provider are always available for hospital edge analysis. Considering constantly rising nursing expenses, it is necessary to have an economic and highly reliable edge solution available that reduces these costs.

 

Data feeds with a timestamp

Fast analysis of series data is business-critical.

Time – we never seem to have enough of it. However, at the same time, series data gets out of control.
Familiar examples are:
– E-commerce applications – storage and analysis of the total value and the place of delivery for an order over time
– Gaming applications – storage and analysis of player actions in a video game
– IT metrics – storage and analysis of IT data (e.g. SLAs, API performance, system metrics)
– Finance applications – storage and analysis of selling price and amount of traded stock (e.g. market index)

Data feeds with a timestamp in TempusDB
Data feeds occur in any form or size and the data itself is usually semi-structured. Thus, it is necessary to have a database adapted to series data with the help of which data can easily be analyzed thanks to range queries. TempusDB is a high-performance, highly failure-resistant NoSQL database which has been optimized for fast reading and writing of data feeds. Data co-location allows fast storing of series data and, together with the possibility of creating tables and running SQL queries, this fact allows a faster analysis of your series data. TempusDB is user-friendly, and in case of rising demand, allows an extension of the capacity with standard hardware. Complicated data sharding is not necessary.

Why you should use TempusDB for data feeds with a timestamp
Regardless of whether your data consists of a set of clicks and views or of data of the financial market, TempusDB ideally stores your series data for fast analysis and real-time reactions. TempusDB has a masterless architecture, high reliability, linear scalability and is user-friendly, all of which is vital for ensuring the constant accessibility of your series data for reading and writing operations.
Retail- and e-commerce companies use TempusDB for storing their series data in order to track order values, collect and analyze social metrics or monitor the positions of vehicles and fuel consumption.
Gaming- and betting companies use TempusDB to follow player actions in their games and to collect and analyze live data from social media in order to make decisions in real-time.
Finance- and insurance companies use TempusDB to store and analyze commodity trade and market data, stock selling prices and -amounts as well as for risk evaluation.

 

Metrics/Log analyses with TempusDB
Metrics and log analyses help to advance your business.
Everyone has their own opinion, but the best decisions are based on data. How can you use log and metric data to make better business decisions? Systems have always also contained log data, but the amount, speed and complexity of these logs have exponentially increased since the spread of IoT sensors and -devices. Furthermore, we are observing an exponential increase of metric analysis. This metric and log files require fast reading and writing operations combined with the possibility of accessing data with range queries –all of this with consistently fast, reliable and scalable systems. With conventional relational databases, this is simply impossible.
Metrics and logs can arrive with a high speed and in a large variety of volume. Some serve as source of information, others require immediate action. Often, a complex analysis is necessary to determine if action is required. Data which looks like information in the beginning can turn out to be a serious issue if the data is aggregated and analyzed after a period of time. TempusDB provides the high performance and reliability needed for the fast analysis of metrics and log data. Data co-location allows fast storage and analysis of semi-structured series data. With TempusDB, range queries can be run so that the cross-system- or cross-device analysis can be limited to certain time spans. In addition, SQL queries make the analysis of your data faster and easier.

Why clients rely on TempusDB as solution for their metrics / log analyses
Across sectors, companies need to store and analyze important metric and log data. Regardless of whether the data is located in system logs, gaming logs of users, weather sensor logs or in health status monitoring systems, easy access and a fast analysis of the data is always necessary. TempusDB processes and stores the most important metrics and log data and makes access and analysis of time-series data as easy as winking.
– Software- and technology companies already cover a wide range, regardless of whether your company is working in the field of social media, security, services or infrastructure: Metric and log data is stored and analyzed. TempusDB enables you to aggregate the data according to time spans and the analysis of system- and equipment problems. In addition, with the help of the system, you can initiate action based on metric analyses, such as system statistics (on/off and CPU) and SLAs (service life and output).
– Gaming- and betting companies log huge quantities of series data, such as performance, statistics and activity of players. TempusDB makes fast range queries and the aggregation of this logged data possible.
– Healthcare providers use their IT infrastructure to connect patients and suppliers. In this infrastructure, huge amounts of logs, metrics and warning messages arise so that these providers use TempusDB for the fast storage and analysis of their serial data. The fast and correct processing of logs and warning messages is of crucial significance in nursing.