What is the difference between hierarchical database and relational database?

Databases are computer programs that store data, or "records." More importantly, they also describe how that data relates to other data in the database. There are many different kinds of database, including hierarchical, network, relational and object oriented. They all serve different purposes, and allow their records to be described in different ways.

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Heirarchical Databases

Hierarchical databases are some of the oldest and simplest kinds of database. They arrange data in a "tree" structure, which is similar to folders and files on a computer. Just as a file on a computer sits in one folder, every record in the database has one "parent." Hierarchically arranged data is often described as having only parent/child relationships.

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Problems with Heirachical Databases

While the hierarchical model is a suitable one for simple structures, it is easy to see how problems might arise, as each "child" can only have one "parent." If the database contained the names of actual parents and their children within a company, you would not be able to describe the fact that both parents of a single child worked for that company. In the language of databases, this would be a "many-to one" (or "many-to-many" if there is more than one child involved) relationship, and hierarchical databases don't describe them well.

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Relational Databases

Relational databases have no problems with many-to-one or many-to-many relationships. Their records are built as multiple "tables," rather than tree structures, and each record on a table has a unique identifier. A company could then have a table with the names of all the parents, a table with the names of all the children, and each record on the parent table could have a relationship with one (or more, or none) of the unique records on the child table--that relationship being "is the parent of." The ability to give records such relationships is what give relational databases their name.

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Advantages of Relational Databases

Relational databases prevent errors by allowing one record to apply to any number of other tables. A child record could be used in a "is the child of" relationship, and the same record could be referred to in a table of "children attending the company picnic." By preventing duplication, the same information can be used in many different ways, without accidentally altering a record.

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Also, relational databases are very good for providing other kinds of data hidden in the records, using queries written in Structured Query Language, or SQL. This enables you to explore the database in ways not immediately apparent, such as finding all the children over a certain age, or all the parents with three or more children.

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Using Hierarchical Databases

It might seem that relational databases are superior to hierarchical ones, and it's true that they are more flexible. But such flexibility is not always necessary for every database. Libraries use hierarchical databases for recording their books, as the Dewey Decimal system is hierarchical in nature. A list of contact phone numbers might be perfectly well served by a hierarchical database. A database is a tool, and the right tool for the job depends on the job at hand.

A hierarchical database is a data model in which data is stored in the form of records and organized into a tree-like structure, or parent-child structure, in which one parent node can have many child nodes connected through links.

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As the name suggests, the hierarchical database model is most appropriate for use cases in which the main focus of information gathering is based on a concrete hierarchy, such as several individual employees reporting to a single department at a company.

The schema for hierarchical databases is defined by its tree-like organization, in which there is typically a root “parent” directory of data stored as records that links to various other subdirectory branches, and each subdirectory branch, or child record, may link to various other subdirectory branches.

The hierarchical database structure dictates that, while a parent record can have several child records, each child record can only have one parent record. Data within records is stored in the form of fields, and each field can only contain one value. Retrieving hierarchical data from a hierarchical database architecture requires traversing the entire tree, starting at the root node

Hierarchical Database vs Relational Database

A relational database is a digital database based on the relational model, which organizes data in sets of tables with columns and rows. The rows, also known as records, represent a collection of related values, and each row is identified by a unique key. Each column holds attributes of a specific data type, and each record typically has a value for each attribute.

The difference between relational and hierarchical databases lies in the data structures. While the hierarchical database architecture is tree-like, data in a relational database is stored in tables with a unique identifier for each record. A relational database structure facilitates easy identification and access of data in relation to other data points in the database. The tables are separate from physical storage structures, which enables database administrators to alter physical data storage without reorganizing the database tables themselves.

Characteristics of hierarchical database models include their simplicity, but also their lack of flexibility. Hierarchical structures, unlike, relational databases, do not describe many-to-one relationships or many-to-many relationships due to the fact that child records can only have a single parent.

Hierarchical Database Model Advantages and Disadvantages

The key advantage of a hierarchical database is its ease of use. The one-to-many organization of data makes traversing the database simple and fast, which is ideal for use cases such as website drop-down menus or computer folders in systems like Microsoft Windows OS. Due to the separation of the tables from physical storage structures, information can easily be added or deleted without affecting the entirety of the database. And most major programming languages offer functionality for reading tree structure databases.

The major disadvantage of hierarchical databases is their inflexible nature. The one-to-many structure is not ideal for complex structures as it cannot describe relationships in which each child node has multiple parents nodes. Also the tree-like organization of data requires top-to-bottom sequential searching, which is time consuming, and requires repetitive storage of data in multiple different entities, which can be redundant.

Does HEAVY.AI Offer a Hierarchical Database Solution?

Analyze hierarchical data structures with the power of HEAVY.AIDB, the foundation of the HEAVY.AI platform. HEAVY.AIDB, an open source, relational, columnar SQL engine, harnesses the parallel processing power of GPUs for interactive visual analytics, and can query up to billions of rows in milliseconds. HEAVY.AIDB is capable of unprecedented data ingestion speeds, making it the ideal SQL engine for the era of big, high-velocity data.

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