How to create an enterprise-level optimized database?

How to create an enterprise-level optimized database

How to create an enterprise-level optimized database

Knowing the process on how to create an optimized database ensures high-performance future data management for companies. The key to this is not in the technology itself, but in the methodology to be developed before and during the creation process.

In fact, according to the 2019 Big Data and AI Executive Survey by NewVantage Partners, 93% of companies find that difficulties in data management are not due to technology, but to personnel, this is due to the methodology based on your work culture.

Recommendations on how to create an enterprise-level database

An enterprise-grade database is a tool that deserves as much attention as possible before creating it. Taking care of each of the steps during the process guarantees a quality final product, this translates into an optimized database with the following characteristics:

  • Provides high data protection and security
  • Returns fast and accurate results to inquiries
  • Ensures a coordinated flow of data in real time
  • Allows multiple user access without affecting data integrity
  • Maintains a coherent and organized structure at all times
  • Eliminate redundancy and save storage space

To achieve these results it is necessary to follow a series of good practices on how to create an enterprise-level database . Some of the most important recommendations are:

  • Analyze the type of company, its commercial nature and its size.
  • Study the commercial and technological objectives of the database.
  • Anticipate the volume of data to handle, as well as the cost and profitability of the management.
  • Contemplate the technological capabilities that the company possesses and those that it must acquire.

How to create a database? Steps to follow

How to create a database is a process delimited by three main stages, which are:

  • Design of the topic base
  • Selection of the type of management system
  • Selection of the most suitable supplier

1. Design process for creating an enterprise-level database

The design of a database is like the architectural plan of a building. It establishes the parameters to follow during creation, implementation and management. The more detailed and careful the design, the higher the quality of the database.

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Thus, this first stage defines, from now on, how to create a database. In this sense, the first three steps within the design are:

  • Define the purpose of the database
  • Establish the types of data to manage
  • Organize your data visualization

a) Define the purpose of the database

Defining the purpose of the database involves looking at it from all possible perspectives. In this way, you can have an idea not only of how to create it, but of how it will be used in the future, what kind of queries will be made about it and what benefits it will bring to its users.

b) Establish the types of data to be managed

Once the purpose of the database is defined, it is then necessary to determine what are the types of data to be managed, how it will be stored and what type of organization and interrelation they will have according to the sources of origin.

c) Organize the data display

According to the types of data to be managed, the way in which these can be consulted and displayed must be organized. Whether users want to access them for reference or for business analytics activities.

After completing the three steps above, another series of steps must be followed during the database design . However, finishing defining how to create a database depends on the type of database to be used, whether it is relational (SQL) or non-relational (NoSQL).

2. Selection of the type of database managing system

During the process of how to create a database one of the most important steps is to define the type of database to implement. The two main models are relational and non-relational databases.

a) Relational databases

Relational databases are those that keep information organized in small segments, relating them to each other through certain parameters. This type of database is characterized by using the SQL language for its queries.

These databases are indicated when it is necessary to comply with the ACID properties in data management: atomicity, consistency, isolation and durability .

Among the main relational databases are:

  • MySQL
  • Oracle
  • SQL Server
  • PostgradeSQL

b) Non-relational databases

Non-relational databases are those that do not maintain a relationship between their data. In this case, the information is organized in documents, which allows for versatility when the nature of the data to be managed is not clear. This type of database is characterized by using languages ??other than SQL for its queries.

These databases are indicated when the information to be managed complies with the so-called ” 3 Vs of big data “: volume, variety and speed.

Among the main non-relational databases are:

  • MongoDB
  • Redis
  • Elasticsearch
  • Cassandra

3. The best providers on the market to create a database

How to create an enterprise-level database depends not only on the technical methodology, but also on knowing how to choose the most suitable management system provider. This selection should be based on all the previous steps, as well as the analysis of the different offers that are in the market.

The technical scalability offered by the providers, their levels of security and data protection, the management environments for the user (on-premise or cloud), the costs, the technologies they have, their additional services such as those of analytics, among others.

In this sense, some of the providers with the most powerful solutions on the market according to the type of database are:

  • Oracle
    • Oracle Autonomous Database (Relational)
    • Oracle Database 18c (relational)
  • Microsoft
    • Access (relational)
    • Azure SQL Database (relational)
    • Azure Database for PostgreSQL (relational)
    • Azure Database for MariaDB (relational)
    • Azure Cosmos DB (non-relational)
  • Amazon Web Services
    • Amazon Aurora (relational)
    • Amazon DynamoDB (non-relational)
    • Amazon DocumentDB ( Document DB)
    • Amazon Neptune (Graphics DB)
    • Amazon Timestream ( Time Series DB for IoT)
    • Amazon QLDB (Accounting DB)
  • IBM
    • Compose for MySQL (relational)
    • Databases for PostgreSQL (relational)
    • Db2 on Cloud (relational)
    • Cloudant (non-relational)
    • Databases for Elasticsearch (non-relational)
    • Compose for JanusGraph (non-relational)
    • Databases for MongoDB (non-relational)
    • Compose for Scylla (non-relational)
    • Databases for Redis (non-relational)
  • Google
    • Cloud SQL (relational)
    • Cloud Spanner (relational)
    • Cloud Bigtable (non-relational)
    • Cloud Firestore (non-relational)
    • Firebase Realtime Database (non-relational)

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