データベースとは？ 定義、使用法、例と種類

What Are Databases? Definition, Usage, Examples and Types Prisma's Data Guide Menu Explore Prisma Want real-time updates from your database without manual polling? Introduction to databases What are databases? Comparing database types: how database types evolved to meet different needs Introduction to database schemas Glossary of common database terminology Data modeling Intro (don't panic) Know your problem space Tables, tuples, types Correctness and constraints Making connections Functional units In vivo: information ecosystems Database types Comparing relational and document databases Relational Databases Document Databases PostgreSQL The benefits of PostgreSQL Getting to know PostgreSQL 5 ways to host PostgreSQL databases Setting up a local PostgreSQL database How to configure a PostgreSQL database on RDS Connecting to PostgreSQL databases Authentication and authorization How to create and delete databases and tables in PostgreSQL An introduction to PostgreSQL data types An introduction to PostgreSQL column and table constraints Working with dates in PostgreSQL Inserting and modifying data Reading and querying data Short guides MySQL 5 ways to host MySQL databases Setting up a local MySQL database Connecting to MySQL databases Authentication and authorization How to create and delete databases and tables in MySQL An introduction to MySQL data types An introduction to MySQL column and table constraints Inserting and modifying data Reading and querying data Tools and utilities Short guides SQLite Setting up a local SQLite database Importing and exporting data in SQLite Creating and deleting databases and tables with SQLite Inserting and deleting data with SQLite How to perform basic queries with `SELECT` with SQLite How to update existing data with SQLite How to export database and table schemas in SQLite Microsoft SQL Server Setting up a local SQL Server database MongoDB What is MongoDB? Setting up a local MongoDB database Connecting to MongoDB databases Introduction to provisioning MongoDB Atlas How to manage users and authentication in MongoDB How to manage authorization and privileges in MongoDB How to manage databases and collections in MongoDB How to manage documents in MongoDB How to query and filter documents in MongoDB Introduction to MongoDB data types Introduction to MongoDB indexes Introduction to MongoDB transactions Introduction to MongoDB connection URIs Working with dates and times in MongoDB How MongoDB encrypts data Introduction to MongoDB database tools & utilities How to sort query results in MongoDB Introduction to MongoDB Aggregation Framework Database tools Top 11 Node.js ORMs, query builders & database libraries in 2022 Top 8 TypeScript ORMs, query builders, & database libraries: evaluating type safety What is connection pooling and how does it work? Managing databases Troubleshooting database outages and connection issues How to spot bottlenecks in performance Syncing development databases between team members Database replication Introduction to OLAP and OLTP How microservices and monoliths impact the database Introduction to database caching Introduction to testing in production Introduction to database backup considerations Introduction to full-text search Serverless architecture What is serverless? Top 13 serverless computing and database providers Introduction to common serverless challenges Traditional databases vs serverless databases Serverless glossary Just for fun The United States' most popular databases by state going into 2022 Introduction to databases What are databases? CONTENT Introduction What are databases? Data persistence vs ephemeral storage Interacting with databases to manage your data What responsibilities do databases have? Alternatives to databases What are databases used for? How do different roles work with databases? How do I work with databases as a developer? Conclusion FAQ Share on Introduction Databases are essential components for many modern applications and tools. As a user, you might interact with dozens or hundreds of databases each day as you visit websites, use applications on your phone, or purchase items at the grocery store. As a developer, databases are the core component used to persist data beyond the lifetime of your application. But what exactly are databases and why are they so common? In this article, we'll go over: what databases are how they are used by people and applications to keep track of various kinds of data what features databases offer what types of guarantees they make how they compare to other methods of data storage Finally, we'll discuss how applications rely on databases for storing and retrieving data to enable complex functionality. What are databases? Databases are logical structures used to organize and store data for future processing, retrieval, or evaluation. In the context of computers, these structures are nearly always managed by an application called a database management system or DBMS . The DBMS manages dedicated files on the computer's disk and presents a logical interface for users and applications. Database management systems are typically designed to organize data according to a specific pattern. These patterns, called database types or database models , are the logical and structural foundations that determine how individual pieces of data are stored and managed. There are many different database types, each with their own advantages and limitations. The relational model , which organizes data into cross-referenced tables, rows, and columns, is often considered to be the default paradigm. DBMSs can make databases they govern accessible via a variety of means including command line clients, APIs, programming libraries, and administrative interfaces. Through these channels, data can be ingested into the system, organized as required, and returned as requested. Data persistence vs ephemeral storage Databases store data either on disk or in-memory. On disk storage is generally said to be persistent , meaning that the data is reliably saved for later, even if the database application or the computer itself restarts. In contrast, in-memory storage is said to be ephemeral or volatile . Ephemeral storage does not survive application or system shutdown. The advantage of in-memory databases is that they are typically very fast. In practice, many environments will use a mixture of both of these types of systems to gain the advantages of each type. For systems that accept new writes to the ephemeral layer, this can be accomplished by periodically saving ephemeral data to disk. Other systems use read-only in-memory copies of persistent data to speed up read access. These systems can reload the data from the backing storage at any time to refresh their data. Backing storage type Data survive restarts? Advantages Examples On disk Yes Data longevity MySQL In-memory No Operational speed memcached Interacting with databases to manage your data While the database system takes care of how to store the data on disk or in-memory, it also provides an interface for users or applications. The interfaces for the database must be able to represent the operations that external parties can perform and must be able to represent all of the data types that the system supports. According to Wikipedia , databases typically allow the following four types of interactions: Data definition : Create, modify, and remove definitions of the data's structure. These operations change the properties that affect how the database will accept and store data. This is more important in some types of databases than others. Update : Insert, modify, and delete data within the database. These operations change the actual data that is being managed. Retrieval : Provide access to the stored data. Data can be retrieved as-is or can often be filtered or transformed to massage it into a more useful format. Many database systems understand rich querying languages to achieve this. Administration : Other tasks like user management, security, performance monitoring, etc. that are necessary but not directly related to the data itself. Let's go over these in a bit more detail below. Data definitions control the shape and structure of data within the system Creating and controlling the structure that your data will take within the database is an important part of database management. This can help you control the shape, or structure, of your data before you ingest it into the system. It also allows you to set up constraints to make sure your data adheres to certain parameters. In databases that operate on highly regular data, like relational databases, these definitions are often known as the database's schema . A database schema is a strict outline of how data must be formatted to be accepted by a particular database. This covers the specific fields that must be present in individual records as well as requirements for values such as data type, field length, minimum or maximum values, etc. A database schema is one of the most important tools a database owner has to influence and control the data that will be stored in the system. Database management systems that value flexibility over regularity are often referred to as schema-less databases . While this seems to imply that the data stored within these databases has no structure, this is usually not the case. Instead, the database's structure is determined by the data itself and the application's knowledge of and relation to the data. The database usually still adheres to a structure, but the database management system is less involved in enforcing constraints. This is a design choice that has benefits and disadvantages depending on the situation. Data updates to ingest, modify, and remove data from the system Data updates include any operation that: Enters new data into the system Modifies existing entries Deletes entries from the database These capabilities are essential for any database, and in many cases, cons