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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. High performance, query optimization, open source and polymorphic data storage are the major Greenplum advantages. Open Source.

Big Data 321
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ScyllaDB Trends – How Users Deploy The Real-Time Big Data Database

Scalegrid

ScyllaDB is an open-source distributed NoSQL data store, reimplemented from the popular Apache Cassandra database. You can run both the free open source ScyllaDB and ScyllaDB Enterprise in the cloud or on-premise, and ScyllaDB Enterprise license starts at $28.8k/year year for a total of 48 cores.

Big Data 187
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Introduction to Grafana, Prometheus, and Zabbix

DZone

Grafana is an open-source tool to visualize the metrics and logs from different data sources. If the data sources are not available then customized plugins can be developed to integrate these data sources. What Is Grafana?

Big Data 161
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What is IT operations analytics? Extract more data insights from more sources

Dynatrace

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Why use a data lakehouse for causal AI? Why is ITOA important? Apache Spark.

Analytics 193
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An overview of end-to-end entity resolution for big data

The Morning Paper

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. Open source ER systems. The survey includes an assessment of open source tools for ER, summarised in the table below.

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Kubernetes for Big Data Workloads

Abhishek Tiwari

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

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Kubernetes in the wild report 2023

Dynatrace

Open-source software drives a vibrant Kubernetes ecosystem. That trend will likely continue as Kubernetes security awareness further rises and a new class of security solutions becomes available. Open source software drives a vibrant Kubernetes ecosystem. Java, Go, and Node.js Kubernetes moved to the cloud in 2022.