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What is Warp 10?

storage

Warp 10 is a platform designed to collect, store and analyze sensor and Time Series data. Warp 10 is both a Time Series Database and an associated analytics environment.

Warp 10 goes beyond simple Time Series by supporting Geo Time Series which result from the fusion of a Time Series of sensor readings with the location of the sensor at each measurement.

The analytics environment offered by Warp 10 is based on a data flow programming language called WarpScript. With a number of available functions exceeding 1000, WarpScript makes Warp 10 the most advanced time series platform.

The solution is hosted on GitHub. If you like it, don’t forget to show your support by adding a star.

Warp 10 Storage Engine

The Time Series Database provided by Warp 10 is called the Warp 10 Storage Engine.

  • Support for the Geo Time Series data model support
  • Built for performance and scalability
  • Secure by design, strong authentication/authorization
  • Use of standard protocols and formats for ease of use

Different versions for different scales

Distributed

Distributed
  • Billions of series
  • Trillions of datapoints
  • Millions of datapoints/s

Standalone

Standalone
  • 10s of millions of series
  • Billions of datapoints
  • ~100k datapoints/s

Edge

Edge
  • Millions of series
  • 100s Millions of datapoints
  • ~10k datapoints/s

Warp 10 Analytics Environment

The analytics environment offers a data flow programming language called WarpScript with more than 1000 functions tailor made for time series data.

The analytics environment smoothly integrates with existing tools and ecosystems with a strong compatibility with everything Hadoop.

Through extension mechanisms, the WarpScript language can be used on time series data hosted in any storage layer, from SQL databases to object stores, including any time series database.

See WarpScript and the WarpScript reference

Learn more about the Data Model

The Warp 10 platform handles a single type of data called Geo Time Series or GTS for short. A GTS is obtained by merging a time series of measurements, a sequence of timestamp/value pairs, with the three time series of the sensor location (latitude, longitude, elevation), at time of the measurement. This handy data structure allows for efficient manipulation of moving sensor measurements. If you do not have location information for your sensors, Warp 10 also support plain old time series.

In order to support the most diverse set of use cases, values of GTS can be of several types: long, double, boolean or UTF-8 string, binary, and even value lists in a single value. You can mix value types in a single GTS, it will be handled at read time when you manipulate the data with the WarpScript language.

Each Geo Time Series is uniquely identified by a class and a set of labels (key/values). The class can be interpreted as the type of sensor, and the labels as uniquely identifying a specific instance in the class. GTS can also have attributes which are another set of key/values, the only difference with labels is that attributes do not identify the GTS, they are simply there to provide additional information, and since they do not identify the GTS they can be modified during the lifetime of the Geo Time Series.

For maximum flexibility, classes and label names and values can be any valid UTF-8 string. If your strings contain characters which are difficult to type, you only have to URL encode your strings using %hh to replace those hard to type characters.

See