Integrating RabbitMQ and MongoDB to Maintain Solr Indexes in Multiple Data Centers
This article details a client success story with using RabbitMQ and MongoDB to Maintain Solr Indexes for high speed, cross data center updates.
News and views on building powerful Search and Business Intelligence solutions.
This article details a client success story with using RabbitMQ and MongoDB to Maintain Solr Indexes for high speed, cross data center updates.
This post breaks down how Mongo addresses the fundamental disparity in how to combine vector search results with lexical search results to maximize the benefits of each.
Setting up a search index isn’t just about indexing data and tying a search box to it, it’s about delivering the right results based on what a person searches for and prioritizing the results they are most likely to want.
Thinking about Spring Batch as your framework for loading a Solr index? With some minor customizations, it won’t take much effort. Picking the correct library and understanding some Solr fundamentals will simplify the endeavor.
How many times have we heard that yelled in our general direction? Search engines, and their teams, are only as good as the data they are given. This is true for all search engines, for all time, regardless of any machine learning algorithms or other bells and whistles they may contain.
We were recently engaged to come up with a simple way to generate Pentaho reports on an Amazon Web Services (AWS) platform. Our client had already created the reports with Pentaho, but preferred not to deploy a full Pentaho BI Server on an EC2 instance. As it happens, this was an excellent opportunity to employ a Lambda function.
Solr has multiple ways of dealing with parent-child relationships, and each have their own features and drawbacks. Here are some of the tips and tricks to consider if you are looking to make a move from Block-Join to a full denormalized solution.
FindTuner’s extensive machine learning and human-touch features enable online retailers to easily meet business objectives while working seamlessly with SAP Commerce and leveraging the search service based on Solr.
Congratulations to the Eclipse Foundation BIRT project team on reviving the project and for its continued development. We’re excited to contribute to BIRT’s progress as the leading open source reporting and data visualization project.
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