hadoop based sql

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Hadoop gives you power and scale via distributed storage (HDFS) and distributed computing (MapReduce). Using SQL gives you ease of use and standards. You can leverage existing Business Intelligence tools and SQL skills your organization already has to query, analyze and visualize your processed Big Data. You can then run standard SQL query which would trigger the MapReduce jobs to process the data on cluster and all the results of processing is stored in relational database, which is readily available to you for further analysis. Once the structured data is assembled, you can query, analyze and visualize this data using standard SQL syntax and other BI tools to achieve your Big Data analytics needs.

TRANSCRIPT

Hadoop Based SQL and Big Data Analytics Solution

Hadoop Based SQL

Hadoop Based SQL and Big Data Analytics Solution

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

• Originally based upon relational algebra and tuple relational calculus, the scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

• Originally based upon relational algebra and tuple relational calculus, the scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.

• SQL is an standard protocol used to request information from databases. Servers which can handle SQL are known as SQL servers.

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

• Originally based upon relational algebra and tuple relational calculus, the scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.

• SQL is an standard protocol used to request information from databases. Servers which can handle SQL are known as SQL servers.

Relational Database

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

• Originally based upon relational algebra and tuple relational calculus, the scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.

• SQL is an standard protocol used to request information from databases. Servers which can handle SQL are known as SQL servers.

Query

Relational Database

What is SQL?

Hadoop Based SQL and Big Data Analytics Solution

• SQL (Structured Query Language) is a special-purpose programming language designed for managing data held in a relational database management system (RDBMS).

• Originally based upon relational algebra and tuple relational calculus, the scope of SQL includes data insert, query, update and delete, schema creation and modification, and data access control.

• SQL is an standard protocol used to request information from databases. Servers which can handle SQL are known as SQL servers.

Query

Data

Relational Database

SQL for Hadoop

Hadoop Based SQL and Big Data Analytics Solution

SQL for Hadoop

Hadoop Based SQL and Big Data Analytics Solution

• Hadoop gives you power and scale via distributed storage (HDFS) and distributed computing (MapReduce).

SQL for Hadoop

Hadoop Based SQL and Big Data Analytics Solution

• Hadoop gives you power and scale via distributed storage (HDFS) and distributed computing (MapReduce). Using SQL gives you ease of use and standards. You can leverage existing Business Intelligence tools and SQL skills your organization already has, to query, analyze and visualize your processed Big Data.

SQL for Hadoop

Hadoop Based SQL and Big Data Analytics Solution

• Hadoop gives you power and scale via distributed storage (HDFS) and distributed computing (MapReduce). Using SQL gives you ease of use and standards. You can leverage existing Business Intelligence tools and SQL skills your organization already has, to query, analyze and visualize your processed Big Data.

• MapReduce uses batches of parallel processing jobs to sort through large volumes of data. SQL, on the other hand, is used with nearly every relational database system and huge numbers of people who know how to use it effectively to mine and analyze data.

SQL for Hadoop

Hadoop Based SQL and Big Data Analytics Solution

• Hadoop gives you power and scale via distributed storage (HDFS) and distributed computing (MapReduce). Using SQL gives you ease of use and standards. You can leverage existing Business Intelligence tools and SQL skills your organization already has, to query, analyze and visualize your processed Big Data.

• MapReduce uses batches of parallel processing jobs to sort through large volumes of data. SQL, on the other hand, is used with nearly every relational database system and huge numbers of people who know how to use it effectively to mine and analyze data.

• Allowing much faster SQL queries at scale makes big data analytics accessible by many more people in the enterprise and fits in with existing workflows.

How QueryIO Converges Hadoop & SQL

Hadoop Based SQL and Big Data Analytics Solution

How QueryIO Converges Hadoop & SQL

Hadoop Based SQL and Big Data Analytics Solution

• It provides a framework which allows you to perform standard SQL queries on your structured and unstructured Big Data. It also provides an easy to use interface through which you can generate SQL queries and design reports to represent your processed big data

How QueryIO Converges Hadoop & SQL

Hadoop Based SQL and Big Data Analytics Solution

• It provides a framework which allows you to perform standard SQL queries on your structured and unstructured Big Data. It also provides an easy to use interface through which you can generate SQL queries and design reports to represent your processed big data

• You can then run standard SQL query which would trigger the MapReduce jobs to process the data on cluster and all the results of processing is stored in relational database, which is readily available to you for further analysis.

How QueryIO Converges Hadoop & SQL

Hadoop Based SQL and Big Data Analytics Solution

• It provides a framework which allows you to perform standard SQL queries on your structured and unstructured Big Data. It also provides an easy to use interface through which you can generate SQL queries and design reports to represent your processed big data

• You can then run standard SQL query which would trigger the MapReduce jobs to process the data on cluster and all the results of processing is stored in relational database, which is readily available to you for further analysis.

• QueryIO also helps making data searchable over Hadoop cluster using SQL. To help make unstructured data searchable on Hadoop Cluster, it stores the metadata for each file stored on Hadoop in a relational database.

How QueryIO Converges Hadoop & SQL

Hadoop Based SQL and Big Data Analytics Solution

• It provides a framework which allows you to perform standard SQL queries on your structured and unstructured Big Data. It also provides an easy to use interface through which you can generate SQL queries and design reports to represent your processed big data

• You can then run standard SQL query which would trigger the MapReduce jobs to process the data on cluster and all the results of processing is stored in relational database, which is readily available to you for further analysis.

• QueryIO also helps making data searchable over Hadoop cluster using SQL. To help make unstructured data searchable on Hadoop Cluster, it stores the metadata for each file stored on Hadoop in a relational database.

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