~~Title: **StreamScape Wiki | Home**~~

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      <font size="+2" color=#990000 style="font-weight:bold;">Real-Time AI</font><br>
      <font size="+1" color=#990000 style="font-weight:bold;">for Cognitive Analytics + Data Science</font><br>
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      Welcome to the documentation portal for StreamScape's Cognitive AI and  <br> 
      Real-Time Analytics Platform and related products. Here you can find the <br>
      information needed to get started with the data engine and learn how to <br>
      develop, manage and deploy streaming, real-time machine AI applications.
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           <img src="/dokuwiki/_media/icons_large/appengine.png" alt="Smiley face" height="46" width="46" style="margin-left:-4px;">
           <a href="/dokuwiki/whats_app" style="margin-right:2em; font-weight:bold; color:#990000">What is Reactive Data?</a>
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           <a href="/dokuwiki/rpl" style="margin-left:6px; font-weight:bold; color:#990000">Reactive Programming in the Cloud</a>
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           <img src="/dokuwiki/_media/icons_large/overview.png" alt="Smiley face" height="36" width="36" >
           <a href="/dokuwiki/basic_concepts" style="margin-left:6px; font-weight:bold; color:#990000">Basic Terms and Concepts</a>
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           <a href="/dokuwiki/basic_concepts" style="margin-left:7px; font-weight:bold; color:#990000">Events and Content Based Addressing</a>
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           <a href="/dokuwiki/getting_started" style="margin-left:6px; font-weight:bold; color:#990000">Quick Start an Engine</a>
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           <img src="/dokuwiki/_media/icons_large/cloudscale.png" alt="Smiley face" height="38" width="38" style="margin-top:2px;">
           <a href="/dokuwiki/basic_concepts" style="margin-left:9px; font-weight:bold; color:#990000">Building Cloud-Scale Applications</a>
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           <img src="/dokuwiki/_media/icons_large/dataspaces.jpg" alt="Smiley face" height="38" width="38" style="margin-left:-2px;">
           <a href="/dokuwiki/basic_concepts" style="margin-left:6px; font-weight:bold; color:#990000">Working with Data in Motion</a>
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           <img src="/dokuwiki/_media/icons_large/sdoedit.png" alt="Smiley face" height="34" width="34" style="margin-left:7px; margin-top:2px;">
           <a href="/dokuwiki/basic_concepts" style="margin-left:6px; font-weight:bold; color:#990000">Data Definition and Validation</a>
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           <img src="/dokuwiki/_media/icons_large/services.png" alt="Smiley face" height="42" width="42" style="margin-left:-2px;">
           <a href="/dokuwiki/basic_concepts" style="margin-left:2px; margin-right:2em; font-weight:bold; color:#990000">Writing and Accessing Services</a>
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           <img src="/dokuwiki/_media/icons_large/api.png" alt="Smiley face" height="34" width="34" style="margin-left:2px; margin-top:4px;">
           <a href="/dokuwiki/basic_concepts" style="margin-left:10px; font-weight:bold; color:#990000">RESTful Web API Authoring</a>
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      <font size="+2" color=#990000 style="font-weight:bold;">Release 3.8</font><br>
      <font size="-1" color=#990000 style="font-weight:bold;">Project Cognos</font><br>
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==== New in this Release === 
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**Version 3.8** introduces new features and enhancements to the engine's core capabilities. Snapshot Tables are high performance Columnar Data Collections that allow for large-scale data compession and probabalistic analysis necessary for Data Science.  An //aggregate processing API// has been fully integrated into the RPL script environment and allows for high-performance computing using a mix of DSQL, Machine Learning and Statistical Functions. 

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{{:wiki:python-logo.gif?200 |}}

A new feature, currently in beta is the Python Co-Processing Module (PCM) that will be available in Q1 of 2023. The PCM is a high-performance, in-memory bridge between Python and the StreamScape data engine. It allows Python programs to ntivley execute in the same adddress space as the data engoine, allowing developers to deploy hundreds of available Machine Learning and AI algorythms available in Python and take advantage of large memory and stream procesing capabilities of the pleaform without changing existing Python code.

[[wp>Data dictionary | Data Dictionary]] and [[wp>Semantic_mapper | Semantic Mapping]] features let users query and work with unstructured documents (ie. JSON, XML, Salesforce Objects), files or tabular data. Data analysts and integrators can make use of the [[wp>Actor_model | Actor Model]] in order to efficiently run parallel queries and process streaming, in-flight data without complicated programming.  

New Drop Box capabilities allow users to exchange file data, map, search and convertdocuments into text format for indexing, Natural Language Processing and Data Minig features of the engine.

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The platform has also been extended to support the following:

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  * [[#tab-stream|Stream Processing]]
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  * [[#tab-jdbc|JDBC]]

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This Wiki site is intended as a work-in-progress and will be updated on a regular basis. If you are interested in 
contributing or subscribing to change notifications, please contact us at [[support@streamscape.com]]. We value your feedback
and contributions.   
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