Graph databases refers to a category of NoSQL databases that represent data whose relations are well represented as a set of nodes. These nodes have an undetermined number of connections and are evaluated through computer algorithms. Good graph database use cases include: Social relationships (nodes are people) Public transport links (nodes can be bus or […]
What Is a Document Database?
Document databases refers to a category of NoSQL that represents data in a tree structure, where paths or branches connect data values or leaves. Frequently, document stores use XML and JSON formats stores. There are few practical limits to the number of paths, fields, values, or types of data that can be added to specific […]
What Is a Key-Value Database?
Key-value databases, also called key-value stores, are often considered the simplest type of NoSQL databases. Each unique identifier is stored as a key with its associated value. The value can be any sort of byte array, data structure, or binary large object (BLOB), and works well for storing enormous amounts of data. Windows Explorer and […]
Demystifying Data Architecture
Ludwig Mies van der Rohe said, “Architecture starts when you carefully put two bricks together”—and Data Architecture begins upon creating, storing, and putting two or more characters together, be they sets of records, emails, pictures, audio, video. This resonated well with initial thoughts about Data Architecture, as it is comprised of things, the functionality of […]
What Is BASE?
BASE describes database processing germane to a NoSQL database, such as a data lake. An increasing number of data volumes and variability, according to DAMA DMBoK, spurred the BASE philosophy. Its popularity rose in 2008. BASE provides less assurance than ACID, but it scales very well and reacts well to rapid data changes. BASE construction […]
Will They Blend? Theobald Meets HANA
Click to learn more about author Maarit Widmann. In the “Will They Blend?” blog series, we experiment with the most interesting blends of data and tools. Whether it’s mixing traditional sources with modern data lakes, open-source devops on the cloud with protected internal legacy tools, SQL with noSQL, web-wisdom-of-the-crowd with in-house handwritten notes, or IoT […]
Tapping the Value of Unstructured Data: Challenges and Tools to Help Navigate
Click to learn more about author Daniel Martin. The amount of data generated in the digital world is increasing by the minute! This massive amount of data is termed “big data.” We may classify the data as structured, unstructured, or semi-structured. Data that is structured or semi-structured is relatively easy to store, process, and analyze. […]
Ten Use Cases to Enable an Organization with Metadata and Catalogs
Click to learn more about author Tejasvi Addagada. Enterprises are modernizing their data platforms and associated tool-sets to serve the fast needs of data practitioners, including data scientists, data analysts, business intelligence and reporting analysts, and self-service-embracing business and technology personnel. However, as the tool-stack in most organizations is getting modernized, so is the variety of […]
Data Is the Driver of NASCAR and F1, and NoSQL Is on Pole
Click to learn more about author Daniel Foulkes Leon. Speed and power are driving the adoption of NoSQL technologies in Motorsports. When it comes to racing and speed, the objectives of Formula 1 and NASCAR teams are the same. Winning. And they aim to do so by having the fastest car, recruiting the most skilled […]
Graph Databases: Updates on Their Growing Popularity
Graph databases became recognized as a database design in 2006, when Tim Bernes-Lee developed the concept of a huge database called the “linked data.” This concept became the basis of graph storage, and could display how organizations, people, and items or entities are associated, or “interconnected” with one another, and the nature of the relationships. […]