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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. It’s architecture was specially designed to manage large-scale data warehouses and business intelligence workloads by giving you the ability to spread your data out across a multitude of servers.

Big Data 321
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Apache Doris vs Elasticsearch: An In-Depth Comparative Analysis

DZone

In the field of big data analytics, Apache Doris and Elasticsearch (ES) are frequently utilized for real-time analytics and retrieval tasks. This article offers a detailed comparison across six dimensions: core architecture, query language, real-time capabilities, application scenarios, performance, and enterprise practices.

Analytics 130
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In-Stream Big Data Processing

Highly Scalable

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. Interoperability with Hadoop.

Big Data 154
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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. We built AutoOptimize to efficiently and transparently optimize the data and metadata storage layout while maximizing their cost and performance benefits.

Storage 212
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What is a data lakehouse? Combining data lakes and warehouses for the best of both worlds

Dynatrace

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? Data management.

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What is a Distributed Storage System

Scalegrid

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130
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Any analysis, any time: Dynatrace Log Management and Analytics powered by Grail

Dynatrace

Limited data availability constrains value creation. Modern IT environments — whether multicloud, on-premises, or hybrid-cloud architectures — generate exponentially increasing data volumes. Teams have introduced workarounds to reduce storage costs. Dynatrace discovers logs automatically at scale.

Analytics 264