When it comes to learning SQL (Structured Query Language), there isn’t a single “best” version of SQL to focus on. SQL is best to learn is a standardized language for managing and querying relational databases, but different database management systems (DBMS) often implement SQL with their own variations and extensions.
Here are a few popular versions of SQL that you can consider learning:
ANSI SQL:
ANSI SQL (American National Standards Institute SQL) is the standardized version of SQL. It provides a common set of syntax and functionality that most DBMSs adhere to in varying degrees. Learning ANSI SQL is best to learn will give you a solid foundation that can be applied to different database platforms.
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MySQL: MySQL is one of the most popular open-source DBMSs, commonly used for web applications. It supports a version of SQL is best to learn that is similar to ANSI SQL, but it also has its own unique features and syntax. MySQL is known for its ease of use and wide adoption.
Oracle: Oracle Database is a robust and widely used commercial DBMS. It has its own version of SQL known as Oracle SQL. If you’re interested in working with enterprise-level databases, learning Oracle SQL can be beneficial.
Microsoft SQL Server: Microsoft SQL Server is a popular DBMS in the Windows ecosystem. It uses a dialect of SQL called Transact-SQL (T-SQL). T-SQL has some unique features and extensions compared to standard ANSI SQL, and it’s well-suited for developing applications on the Microsoft technology stack.
PostgreSQL: PostgreSQL is a powerful open-source DBMS that supports a version of SQL similar to ANSI SQL. It is known for its advanced features, extensibility, and strong adherence to SQL standards.
SQLite: SQLite is a lightweight, file-based relational database management system. It is widely used in embedded systems, mobile applications, and as an in-memory database. SQLite uses a version of SQL that is similar to ANSI SQL and is known for its simplicity and small footprint.
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IBM Db2:
IBM Db2 is a widely used commercial DBMS that offers support for large-scale enterprise applications. It has its own version of SQL called Db2 SQL, which includes additional features and optimizations specific to IBM’s database technology.
MariaDB: MariaDB is an open-source relational DBMS that is compatible with MySQL. It was created as a community-driven fork of MySQL is best to learn and offers similar SQL syntax and functionality. Learning MariaDB SQL can be useful if you’re interested in working with MySQL or MariaDB databases.
Amazon Redshift: Amazon Redshift is a cloud-based data warehousing service provided by Amazon Web Services (AWS). It uses a variant of SQL called Amazon Redshift SQL, which is based on PostgreSQL. If you’re interested in working with data warehousing and analytics, learning Amazon Redshift SQL is best to learn can be valuable.
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IBM Informix: IBM Informix is a powerful and feature-rich DBMS known for its high-performance capabilities. It has its own variant of SQL called Informix SQL, which includes unique features and optimizations specific to the Informix database.
SAP HANA: SAP HANA is an in-memory data platform that offers real-time analytics and high-speed data processing. It uses a version of SQL called SAP HANA SQL or HANA SQLScript. Learning SAP HANA SQL can be beneficial if you are working with SAP HANA or planning to work with SAP’s enterprise solutions.
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Teradata:
Teradata is a popular data warehousing platform known for its scalability and parallel processing capabilities. It uses a variant of SQL called Teradata SQL. If you are interested in working with large-scale data warehousing projects, learning Teradata SQL can be valuable.
Snowflake: Snowflake is a cloud-based data warehousing platform that offers scalability and flexibility. It supports a variant of SQL that is similar to ANSI SQL, with some additional features specific to Snowflake’s architecture. Learning Snowflake SQL can be useful if you plan to work with Snowflake as your data warehousing solution.
IBM SQL/DS and DB2:
IBM SQL/DS and DB2 are widely used commercial DBMSs. They have their own versions of SQL, known as SQL/DS and DB2 SQL, respectively. Learning these versions of SQL can be beneficial if you’re interested in working with IBM database systems.
Sybase ASE: Sybase ASE (Adaptive Server Enterprise) is a robust DBMS known for its high-performance capabilities. It uses a version of SQL called Transact-SQL (T-SQL), which is similar to Microsoft SQL Server’s dialect. Learning Sybase ASE SQL can be advantageous if you’re planning to work with Sybase or in environments where Sybase databases are prevalent.
MongoDB: While not a traditional relational database, MongoDB is a popular NoSQL document database. It uses a query language called MongoDB Query Language (MQL) or MongoDB Query API, which is different from SQL. If you’re interested in working with NoSQL databases, specifically MongoDB, learning MQL can be valuable.
Apache Hive: Apache Hive is a data warehousing infrastructure built on top of Apache Hadoop. It provides a SQL-like query language called Hive Query Language (HQL), which translates SQL-like queries into MapReduce or Tez jobs for processing large datasets. Learning HQL can be useful for working with big data and distributed computing.
MemSQL: MemSQL is an in-memory distributed DBMS that combines the benefits of a relational database with real-time analytics. It supports a version of SQL similar to ANSI SQL, with additional features optimized for in-memory processing. Learning MemSQL SQL can be beneficial if you’re interested in working with high-performance, real-time data processing systems.
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IBM Netezza:
IBM Netezza is a data warehousing appliance known for its high-performance analytics capabilities. It uses a variant of SQL called Netezza SQL, which includes optimizations for parallel processing and query performance. Learning Netezza SQL can be beneficial if you work with Netezza appliances or need to optimize queries for high-speed data analysis.
Google BigQuery: Google BigQuery is a fully managed, serverless data warehouse provided by Google Cloud. It supports a variant of SQL called BigQuery SQL, which extends standard SQL with additional features for distributed data processing. Learning BigQuery SQL can be useful for working with large-scale data analytics projects in the Google Cloud environment.
Apache Cassandra:
Apache Cassandra is a highly scalable and distributed NoSQL database. It uses a query language called CQL (Cassandra Query Language), which has SQL-like syntax but differs significantly from traditional SQL. If you’re interested in working with NoSQL databases, specifically Apache Cassandra, learning CQL can be valuable.
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