Operations | Monitoring | ITSM | DevOps | Cloud

August 2023

Data Lake vs Data Warehouse

Data warehouses and data lakes represent two of the leading solutions for enterprise data management in 2023. While data warehouses and data lakes may share some overlapping features and use cases, there are fundamental differences in the data management philosophies, design characteristics, and ideal use conditions for each of these technologies.
Sponsored Post

Serverless Elasticsearch: Is ELK or OpenSearch Serverless Architecture Effective?

Here's the question of the hour. Can you use serverless Elasticsearch or OpenSearch effectively at scale, while keeping your budget in check? The biggest historical pain points around Elasticsearch and OpenSearch are their management complexity and costs. Despite announcements from both Elasticsearch and OpenSearch around serverless capabilities, these challenges remain. Both of these tools are not truly serverless, let alone stateless, hiding their underlying complexity and passing along higher management costs to the customer.

What is a Real-Time Data Lake?

A data lake is a centralized data repository where structured, semi-structured, and unstructured data from a variety of sources can be stored in their raw format. Data lakes help eliminate data silos by acting as a single landing zone for data from multiple sources. But what’s the difference between a traditional data lake and a real-time data lake?

How Gaming Analytics and Player Interactions Enhance Mobile App Development

The number of mobile game users is expected to increase to 2.3 billion users by 2027, with a CAGR of 7.08%. The resulting projected market volume is a staggering $376.7 billion by 2027. Competition is fierce, and differentiation is key to winning out in this rapidly growing market. To understand their users and build better games, gaming companies need to use data analytics to interpret how players interact with their games. Effective use of video game data can help companies.

Data Retention Policy Guide

Data retention policy will become a major focus for CIOs in 2021. Here’s why: First, enterprise organizations are producing larger volumes of data than ever before and utilizing enterprise data across a wider range of business processes and applications. To maximize its value, this data must be managed effectively throughout its entire life cycle - from collection and storage, through to usage, archiving, and eventually deletion.