With the explosive growth of enterprise data, cross-department, cross-application, and cross-platform data interaction requirements are becoming more and more frequent, and traditional data query methods are no longer able to meet these needs. At the same time, there are differences in data formats and query languages between different database systems, making it very difficult to directly conduct cross-database queries.
Limitations of native cross-database queries
Although database systems such as MySQL, Oracle, and PostgreSQL all provide their own cross-database query functions, they have many limitations:
- Database type restriction: MySQL's Federated and Oracle's Database Links functions both require that the target database must also be the same type of database, which limits the scope of application of the cross-database query function. Not suitable for cross-database queries of heterogeneous databases.
- Performance loss: The built-in cross-database query function may introduce performance loss, especially when large-scale data query or data transmission, it will increase query time and system burden. Affect query efficiency.
- Differences in syntax and semantics: The built-in cross-database query functions of different database systems have different syntaxes. You need to learn and understand different query syntax and mechanisms.
- Security and privacy issues: The built-in cross-database query function may provide limited support for data privacy and security control, making it difficult to achieve desensitization or strict access to sensitive data. Permission control may lead to the risk of data leakage.
- Limited to network environment: The built-in cross-database query function may have certain requirements on network delay, stability and bandwidth, and may have limitations on applications in complex network environments. .
- Lack of graphical interface support: The cross-database query function that comes with most database systems lacks an intuitive and graphical interface. You often need to operate in the dark, which reduces the user experience and efficiency.
Taken together, these limitations mean that the cross-database query function that comes with the database system may not be able to meet complex and diverse data analysis needs, especially in scenarios such as heterogeneous databases, large-scale data queries, and high-performance and high-security requirements. .
What is NineData DSQL?
NineData DSQL is a cross-database query function for multiple homogeneous database systems. It currently supports SELECT operations on tables and views. You can access multiple databases in one query, obtain useful information scattered in various databases, and aggregate this information into one query result to easily cross multiple databases, multiple data sources, and even multiple heterogeneous databases. Construct data query of data source.
NineData DSQL has the following features:
- Connect multiple database systems: Supports connection to multiple database systems and ensures compatibility between these database systems. These database systems can come from different vendors or platforms, and there can be differences in data formats, storage methods, query languages, etc.
- Uniform query syntax: DSQL provides a unified query syntax. You only need to use one syntax to query across multiple heterogeneous or homogeneous databases, and the system will Automatically parse and convert this syntax into query syntax for different types of data sources for issuing queries.
- Result integration and output: Integrate query results from homogeneous and heterogeneous database systems and unify the output format to facilitate you to obtain the information you need. You don't need to care about which database the data is stored in, you can get the results you want with just one query.
- Data privacy and security protection: Based on NineData's permission management function, it supports desensitization of sensitive data, control of access permissions, etc., to protect the privacy and security of data. Prevent data leakage and illegal access.
- Graphical interface support: Provides a clear graphical interface to facilitate your visual query and management and improve your work efficiency.
Easy-to-remember DSQL query syntax
In DSQL, whether you are executing a joint table (view) query or a single table (view) query, you need to use a three-part syntax when specifying the source data source, that is, <DBLINK name>.<Library name|Schema name> ;.<Table name (view name)>.
Example 1: Query across heterogeneous sources, querying data from DBLINK1 (MySQL) and DBLINK2 (Oracle).
SELECT *
FROM DBLINK1.database_name.table_name a,
DBLINK2.schema_name.table_name b
WHERE a.id=b.id;Example 2: Single table (view) query, query data from DBLINK1.
SELECT *
FROM DBLINK1.database.table_name
WHERE id=1;If your library name or table (view) name starts with a number, or uses a reserved field, you need to wrap the name in double quotes (""), otherwise the query will fail. For example:
SELECT * FROM dblink_mysql_3451."9zdbtest3".sbtest1;When do you need to use DSQL?
- Enterprise-level data integration: Enterprises often need to integrate data from multiple departments or systems to provide a more comprehensive view. Through DSQL, enterprises can access multiple databases in one query, obtain useful information scattered in various databases, and then integrate them together to facilitate data analysis and decision-making.
- Data Mining and Analysis: Data mining and analysis require a large amount of data support. With DSQL, you can retrieve the data you need from multiple databases, and then use mining and analysis tools to conduct in-depth research and analysis of the data.
- Data Warehouse: A data warehouse is a system used to store and manage large amounts of data. Through DSQL, you can realize the functions of a data warehouse without building a data warehouse.
Operation example
5.1 View the database table column information that needs to be queried
You can view the DBLink name, library name | Schema name, table name, view name, column name and other information you need to query in the left navigation bar without having to operate in the dark.
View the database table column information that needs to be queried
5.2 Write cross-database query statements and execute them
Multiple homogeneous and heterogeneous data sources can be queried through simple query SQL, and sensitive fields in the query results can be desensitized.
Write cross-database query statements and execute them
5.3 Integrate multi-table query results and export them
After executing a cross-database query, the system will integrate the query results into a table, and you can export the result set. At the same time, it also supports searching the result set.
Integrate multi-table query results and export them
5.4 Collection of commonly used DBLinks
If there are many DBLinks, you can save several commonly used DBLinks for easy search.
Favorite commonly used DBLink
To sum up, NineData DSQL provides a global perspective on your data, improves data utilization while reducing the complexity of data processing, and provides enterprises with a more flexible, efficient and secure way to process data. Promote data-driven decision-making and business development, helping enterprises reduce costs and increase efficiency.