Hands-On

Demo Video: LeanXcale for Real-Time Spatial Applications
If you are familiar with our previous posts, you probably know about the many disruptive features available in LeanXcale. Linear
Connecting LeanXcale with R
Hi! In this post, I demonstrate how to connect an R application to a LeanXcale database with the LeanXcale JDBC
How to synchronize MySQL with other Relational DB Using Debezium (II)
In this post, we continue working with Debezium and LeanXcale configured for a common client scenario that has a large
How to synchronize MySQL with other Relational DB Using Debezium (I)
One important requirement many clients ask us to work on with LeanXcale is to have an instance running in parallel
Building a CSV Data Loader to Explore COVID-19 Data
I want to share how to build a simple loader for CSV files using statistics that show the COVID-19 evolution
Kafka Connector for LeanXcale (II)
As promised, here is the continuation of the post about the Kafka connector for LeanXcale. Let's see how to execute it!
Kafka Connector for LeanXcale (I)
As a crucial component of the toolset required to establish an effective operational or Big Data architecture with LeanXcale, we
Configuring LeanXcale for your Deployment
This article explains how LeanXcale is deployed to adjust its components to different types of workloads. LeanXcale is a database
Online Aggregations in LeanXcale
To improve its behavior as a transactional and analytical processing (HTAP) database, LeanXcale provides a new feature for supporting online
Connecting LeanXcale with SCALA
Hi! Welcome back! In this new post, I will show you how to connect your Scala application to a LeanXcale
Building a Movie-Recommendation Engine with Spark and LeanXcale
This post demonstrates how to combine the use of Apache Spark and LeanXcale to build a simple movie-recommendation engine, taking
From MEAN to LEAN
In this post, I will show how we can use the LeanXcale database to build a web application following the
YCSB – LeanXcale vs MariaDB
MariaDB is one of the most popular and widely adopted relational databases in the world. LeanXcale is an ultra-scalable relational
Scalable GIS on LeanXcale
New applications, such as geo-marketing tools, car-sharing, or mobility apps, require handling large data volumes. Traditionally, most applications that require
Bi-Dimensional Partitioning: The Key for Performance in Growing Time-Series Data
KEY CONCEPTS A database is essentially "an organized collection of data." Of course, this idea of being “organized" holds an
MVCC – Managing Old Versions in LeanXcale vs PostgreSQL
In the world of databases, most people have encountered some “hidden” processes executed in the background resulting in the spoiling
How to Configure a Local LeanXcale Environment with Docker and Docker Compose
In this post, I show how to set up a local LeanXcale environment using Docker and Docker Compose for development
YCSB – KiVi vs DynamoDB
Today, NoSQL databases are widely used with key-value datastores being one of the most used of all database varieties. The
Linear Scalability, the Bottleneck of SQL Databases
INTRODUCTION Today, companies are storing more data compared to years ago, which creates a need for systems capable of storing
GIS Support on LeanXcale
Geospatial data refers to objects (in the wide sense of the object word) that may have a representation on the
Tweet Sentiment Analysis on a LeanXcale Database
In previous posts, we showed how to stream Twitter data into a LeanXcale database using a direct API. In today's post,
Streaming Twitter Data into a LeanXcale Database
Recently, I read a post about streaming Twitter data into a MySQL database to filter and store tweets for further analysis. Today,