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1. Become a Quantexa deployment wizard! - launching Quantexa's Deployment Engineering Best Practices!
Want to know neat tricks for deploying Quantexa? Our architects have distilled their favorite deployment learnings into the best practice section on the documentation site which will help you deliver and run high quality Quantexa deployments. These learnings come from deploying Quantexa over many years at dozens of…
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1. Introducing QPython
In this article, we'll introduce QPython and give some examples of how your data scientists could use it for interacting with the Quantexa platform. The Quantexa Decision Intelligence Platform is a powerful tool underpinned by a set of capabilities for performing complex analytics with Quantexa-processed data, such as…
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1. Multi Use Case Best Practice
The Quantexa Platform is not a point solution; it has been developed on fundamental principles of flexibility and scalability, and supports multiple business applications or use cases in a single system. Many Quantexa deployments will originally serve a single use case, although some may be intended for broader use from…
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1. Release Notes overview
Our Release Notes have everything you need to know about the features, capabilities, fixes, and improvements in each release of The Quantexa Platform, so it's a very important and popular area of our Documentation Site. On Community, you'll find the latest Release Notes in the release announcements category. What can I…
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1. Setting Up Infrastructure and Underlying Platforms
Based on our experience working with a wide variety of environments, we have several of recommendations for setting up the underlying platforms for a Quantexa deployment. These recommendations help you optimize the cost, maintainability, and reliability of your Quantexa deployments. Due to the fundamental differences in…
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1. Using Quantexa Kafka Streaming for the First Time
Quantexa integrates Kafka as its primary streaming platform to process, ingest, and generate networks in near real-time, leveraging its powerful Entity Resolution, and Big Data capabilities. Quantexa provides out-of-the-box applications such as Kafka Record-Extraction and Kafka Document-Ingest, designed to streamline data…
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2. Designing a Kafka Solution to Meet Functional and Non-Functional Requirements Beyond Quantexa
Designing a Quantexa streaming solution that addresses both functional and non-functional requirements can be challenging, especially when specific use cases require capabilities beyond the OOB functionalities of Quantexa platform. While some extensions may be necessary to meet these requirements, it is crucial to avoid…
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2. Elasticsearch Considerations For Quantexa
This article discusses the key considerations for solution architects and data engineers when deploying Elasticsearch (sometimes referred to as Elastic) for Quantexa. It's useful, though not essential, to have a high level understanding of Quantexa in general, such as how we use Document, Entity and Compounds. 💡Notes /…
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2. Multi Use Case Best Practice: People
This page describes Quantexa's people-related recommendations for multi use case deployments. Many of the practices described on this page will also benefit single use case deployments. These best practices are: Identify a single platform owner for the whole Quantexa service. Form a Design Authority to set the technical…
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2. Quantexa Deployment Patterns Best Practice
Introduction Quantexa deployments require a simple set of underlying components: Distributed Spark cluster for Quantexa batch data processing Container platform to serve the Quantexa UI and microservices Elasticsearch for serving data to the application-tier RDBMS for storing user state in the application-tier Along side…