Systems | Development | Analytics | API | Testing


How To Set Up Elasticsearch on Heroku

Use Elasticsearch Features on HerokuPower your data collection and analysis processes with Elasticsearch on Heroku. While Heroku streamlines your app developing process, this search engine add-on allows data analysts and app developers to manage, sort, and analyze information in near real-time. Explore the benefits of these two tools and how provides innovative data integration.

Full-Text Search for Ruby on Rails with Litesearch

In this post, we'll turn to the last piece of the puzzle in LiteStack: Litesearch. As an example, we will equip a prompts index page with a search bar to query a database for certain prompts. We will generate a couple of fake records to test our search functionality against. Let's get to it!

The Evolution of Search: How Multi-Modal LLMs Transcend Vector Databases

As we venture deeper into the data-driven era, the traditional systems we have employed to store, search, and analyze data are being challenged by revolutionary advancements in Artificial Intelligence. One such groundbreaking development is the notable advent of Large Language Models (LLMs), specifically those with Multi-Mod[a]l abilities (e.g., Image & Audio).

Understanding the Elasticsearch Query DSL: A Quick Introduction

Elasticsearch is a distributed search and analytics engine that excels at handling large volumes of data in real time. When we have such a large repository of data, singling out the most suitable context can be a grueling task. And precisely that’s why we query. Querying allows us to search and retrieve relevant data from the Elasticsearch index with relative ease. Elasticsearch uses query DSL for this purpose. Query DSL is a powerful tool for executing such types of search queries.

Getting Started with Elasticsearch Mapping

Elasticsearch Mapping is a process of defining the schema or structure of the data that is going to be indexed and searched. Mapping determines how Elasticsearch will interpret and handle the data being indexed, including the field names, data types, and how they are analyzed and indexed for search. Mapping in Elasticsearch is essential for ensuring that the data is indexed and searched accurately and efficiently.

Beginner's Guide to Elasticsearch API: Indexing and Searching Data

Elasticsearch is a JSON-based database leaning heavily towards the unstructured types within the databases available out there. ( Postgres and MySQL are purely structured, while NoSQL is entirely unstructured). It interacts through restful APIs and provides a central unit system combining several datasets arising out of logs, metrics, and application trace data. A quick comparison with relational database management systems (RDBMS) will tell us their similarities.

How to Debug an Unresponsive Elasticsearch Cluster

Elasticsearch is an open-source search engine and analytics store used by a variety of applications from search in e-commerce stores, to internal log management tools using the ELK stack (short for “Elasticsearch, Logstash, Kibana”). As a distributed database, your data is partitioned into “shards” which are then allocated to one or more servers.