Importance of time-series analysis for organizations
User clicks in a website; asset monitoring; security systems; business metrics. What is the common ground among all of those data uses? To all of them, it’s very important to know when stuff happened. They generate what we call time series data. Time series data is a sequence of data points collected at regular intervals over a period of time, that usually save data coupled with a timestamp.
Though the concept and use of time series data are not new, the large growth in IoT has driven up the demand to process and analyze large volume of time-series data. The main point about time series data is the order of time points matters. Time-series data are analyzed to determine the long-term trend in order to predict the future or perform some other form of time-dependent analysis.
Problems when using different solutions
Traditional relational databases were not built to handle the volume, speed, and variety of data being generated by devices and sensors. They can also be very expensive, since you pay for storage space and performance, and time series data usually demands a lot from both. This causes big challenges in inserting, storing and analyzing this type of data.
How SlicingDice completely solve these challenges
Knowing the importance of analyzing this type of data, we built our All-In-One solution as a cloud-based data warehouse ready to ingest and analyze billions of time series data points from multiple sources in a very fast, cheap and easy way.
SlicingDice offers a petabyte-scale analytical data warehouse which is the ideal choice for storing time series data since it was built for that. Coupled with our innovative pay-per-column pricing model, where you can store unlimited rows per column for a fixed price, this means organizations can store as much data as they need, with low and predictable costs.
Since time-series data can be used in a lot of different cases, we support both time-series and non-time-series data without losing performance or adding complexity, so analytics can be easily performed to meet any analytical use case. As we’re All-in-One, organizations can save time and money by using a single solution to handle all their different data types and uses, freeing IT personnel to perform other, more business-critical tasks.
Unlimited data storage.
Store unlimited events for the same metric, paying a fixed price for each different column you use.
Schema and data type flexibility.
Store time series and non-time series in the same database. Store data with different structures. Query it all together for deeper insights.
SQL & API flexibility.
Interact with your database using both SQL and our REST API. Perform any task the way it best fits your needs.
Real time streaming and visualization.
Stream data and analyze it in real time. Perform queries and see dashboards updated as fast as you need.