Developer Vocabulary Flashcards
AWS Redshift
Amazon Redshift is an Internet hosting service and data warehouse product which forms part of the larger cloud-computing platform Amazon Web Services. It is built on top of technology from the massive parallel processing (MPP) data warehouse company ParAccel (later acquired by Actian),[1] to handle large scale data sets and database migrations.[2] Redshift differs from Amazon’s other hosted database offering, Amazon RDS, in its ability to handle analytic workloads on big data data sets stored by a column-oriented DBMS principle.
Amazon Redshift is based on an older version of PostgreSQL 8.0.2, and Redshift has made changes to that version.
Quicksight
Amazon product with pay per session.
Amazon QuickSight is an Amazon Web Services utility that allows a company to create and analyze visualizations of its customers’ data. The business intelligence service uses AWS’ Super-fast, Parallel, In-memory Calculation Engine (SPICE) to quickly perform data calculations and create graphs.
Domo
Overview. Domo, Inc is a cloud-based platform designed to provide direct, simplified, real-time access to business data for decision makers across the company with minimal IT involvement.
Josh James
GCP
Google Cloud Platform
Google Cloud Platform, offered by Google, is a suite of cloud computing services that runs on the same infrastructure that Google uses internally for its end-user products, such as Google Search and YouTube.
Microservices
Microservices are a software development technique—a variant of the service-oriented architecture architectural style that structures an application as a collection of loosely coupled services. In a microservices architecture, services are fine-grained and the protocols are lightweight.
PostgreSQL
PostgreSQL is an open-source relational database management system emphasizing extensibility and standards compliance. It can handle workloads ranging from single-machine applications to Web services or data warehousing with many concurrent users.
Relational database vs Document database
In a relational database system you must define a schema before adding records to a database. The schema is the structure described in a formal language supported by the database and provides a blueprint for the tables in a database and the relationships between tables of data. Within a table, you need to define constraints in terms of rows and named columns as well as the type of data that can be stored in each column.
In contrast, a document-oriented database contains documents , which are records that describe the data in the document, as well as the actual data. Documents can be as complex as you choose; you can use nested data to provide additional sub-categories of information about your object. You can also use one or more document to represent a real-world object. The following compares a conventional table with document-based objects:
Kubernetes
Kubernetes is an open-source container orchestration system for automating application deployment, scaling, and management. It was originally designed by Google, and is maintained by the Cloud Native Computing Foundation.
Index
Something I want to be able to sort by frequently; keeps things organized; calculating stuff in advance so in the future it happens instantly.
A common method for keeping track of data so that it can be accessed quickly. Like an index in a book, it is a list in which each entry contains the name of the item and its location.
Data Lake
A data lake is a system or repository of data stored in its natural format, usually object blobs or files. A data lake is usually a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as reporting, visualization, analytics and machine learning.
WCAG
Web Content Accessibility Guidelines (WCAG) 2.0
