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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. In this blog post, we explain what Greenplum is, and break down the Greenplum architecture, advantages, major use cases, and how to get started. The Greenplum Architecture. The Greenplum Architecture.

Big Data 321
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Ready for changes with Hexagonal Architecture

The Netflix TechBlog

At one point, more than 30 developers were working on it, and it had well over 300 database tables. Leveraging Hexagonal Architecture We needed to support the ability to swap data sources without impacting business logic , so we knew we needed to keep them decoupled. The dependency graph in Hexagonal Architecture goes inward.

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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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AWS serverless services: Exploring your options

Dynatrace

To get a better understanding of AWS serverless, we’ll first explore the basics of serverless architectures, review AWS serverless offerings, and explore common use cases. Serverless architecture: A primer. Serverless architecture shifts application hosting functions away from local servers onto those managed by providers.

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Comparing PostgreSQL DigitalOcean Performance & Pricing – ScaleGrid vs. DigitalOcean Managed Databases

Scalegrid

ScaleGrid is a fully managed DBaaS that supports MySQL, PostgreSQL and Redis™, along with additional support for MongoDB® database and Greenplum® database. Along with many popular cloud providers, DigitalOcean also provides a Managed Databases service. So, which database service is right for your application? Single Node.

Database 230
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases.

Storage 297
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Designing Instagram

High Scalability

Architecture. We will use a graph database such as Neo4j to store the information. Additionally, we can use columnar databases like Cassandra to store information like user feeds, activities, and counters. After that, the post gets added to the feed of all the followers in the columnar data storage. High Level Design.

Design 334