THE TIME SERIES PLATFORM

Shapelets provides a range of features that enable users to make the most of time series data in an easy and simple way.

OPEN PLATFORM: CONNECT, PLUG & PLAY

From data collection, storage, analysis and data visualisation, Shapelets integrates seamlessly with streams of data, data at Rest, BI tools and MS Office.

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Bring data

Bring your own data

Shapelets reads data wherever it may be. Retrieve streams of data from sensors, network logs, web clickstreams, social media, etc. from systems such as:


  • MQTT, Kafka, TCP, HTTP, E-Mail, Files, etc.

    Shapelets can also ingest batch data at rest via Apache Drill from databases and file systems like.


  • HBase, MongoDB, MapR-DB, HDFS, Amazon S3, Azure Blob Storage, Google Cloud Storage, Swift, NAS and local files

    Shapelets acts as an intelligent distributed cache with write-through and read-through behaviours.

Native storage

...or use our native storage

Shapelets offers the possibility to act as your primary data source not only for time series information but also for all the additional data surrounding your sequences.


By using Shapelets Native Storage, you can reduce the complexity of your production environment, by decommissioning existing servers, licenses and additional production costs and resulting in a better ROI model.


When data storage is natively provided by Shapelets, external systems can still access the data either through API calls, Shapelets Flow or, directly, through a standard SQL-99 interface.

Distributed core

Shapelets Distributed Core

Shapelets is a distributed system where each node in the cluster provides the same set of services like memory-centric APIs, durable store (if enabled), streaming and execution services.


Shapelets’ memory centric cluster works alongside different layers. The inner core is a subset of the nodes that hold durable data and the outer layers can appear and disappear on demand. This architecture minimises rebalancing data operations whilst giving the ability to scale dynamically the number of computational and streaming nodes.


The Shapelets ML engine executes algorithms moving the computation to the data. When this is not possible, our engine assign tasks to make the best of the resources available in a parallel fashion.

Microsoft office

BI and Microsoft Office Integration

Shapelets offers a simple REST API so users can publish their analytics into their custom time series visualizations tools.


Business users, analysts and data scientists can use standard BI/analytics tools such as Tableau, Qlik, MicroStrategy, Spotfire, SAS and Excel.


Our Cristal UI can also export dashboards that can be hosted within Microsoft PowerPoint and Excel, making your analysis portable in your presentations.

TRY KHIVA!

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Join our community and contribute with the largest library of algorithms for time series

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