Apache Spark™ is considered as the most powerful engine for executing data engineering, data science, and machine learning on single-node machines or clusters over diverse data sources such as NoSQL databases.

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Spark Streaming is an extension of the core Spark API that enables scalable, high-throughput, fault-tolerant stream processing of live data streams. Data can be ingested from many sources like Kafka, Kinesis, or TCP sockets, and can be processed using complex algorithms expressed with

Apache Spark is a fast and general computing engine used for big data processing. It can process data from different sources and formats, one of them is data from relational databases like PostgreSQL.

In our article, we will show you the steps to on how to read data from PostgreSQL t

MongoDB classified as a NoSQL document database with the scalability and flexibility that developers require for querying and indexing most complex data applications at any scale.

MongoDB stores data in flexible, JSON-like documents with optional schemas (schema-less), meani

The open source, in-memory data store used by millions of developers as a database, cache, streaming engine, and message broker.

Redis is a data structure server. At its core, Redis provides a collection of native data types that help you solve a wide variety of prob

Data Structures

Data Engineering

Algorithms

Data Science

Linux

Using Red Hat Satellite to configure hosts with Ansible playbooks and roles

Controlling pod placement onto nodes in OpenShift

Create a storage class for NFS dynamic storage provisioning in OpenShift

Windows management with Ansible

Track down space in Linux

Running Spark on Kubernetes with AKS

Data Lakehouse, The Best of Both Worlds

CAP Theorem, Does it still hold in modern days

Pandas API over Pyspark