Amit Ganesh

What is he best known for?

The fields of study he is best known for:

• Database
• Operating system
• Programming language

Amit Ganesh mainly investigates Database, Database server, Table, Set and Row. His work carried out in the field of Database brings together such families of science as Operating system and Undo. His Database server research integrates issues from Distributed database, Database testing, Database tuning, Remote Database Access and Database design.

His Table study combines topics from a wide range of disciplines, such as Data access, Computer hardware and Index. He has researched Set in several fields, including Object, Adaptive filter and Information retrieval. His Row research focuses on Computer graphics and how it connects with Column.

His most cited work include:

• Generating continuous query notifications (109 citations)
• System and method for data de-duplication (106 citations)
• Query and exadata support for hybrid columnar compressed data (103 citations)

What are the main themes of his work throughout his whole career to date?

Amit Ganesh mostly deals with Database, Set, Data mining, Row and Parallel computing. His work on Database server, Database transaction and Transaction data as part of general Database study is frequently linked to Volatile memory, bridging the gap between disciplines. His study looks at the relationship between Database server and fields such as Metadata, as well as how they intersect with chemical problems.

Amit Ganesh interconnects Algorithm, Real-time computing and Relational database management system in the investigation of issues within Set. His studies examine the connections between Data mining and genetics, as well as such issues in Information retrieval, with regards to Data classification. His research integrates issues of Computer graphics and Table in his study of Row.

He most often published in these fields:

• Database (48.21%)
• Set (16.96%)
• Data mining (13.39%)

What were the highlights of his more recent work (between 2011-2020)?

• Database (48.21%)
• Parallel computing (12.50%)
• Database server (12.50%)

In recent papers he was focusing on the following fields of study:

Amit Ganesh mainly focuses on Database, Parallel computing, Database server, Volatile memory and Set. In the subject of general Database, his work in Database design is often linked to Bitstream format, thereby combining diverse domains of study. His Parallel computing research incorporates elements of Granularity, Column and Table.

His work deals with themes such as Object, Metadata and Row, which intersect with Database server. His Set study integrates concerns from other disciplines, such as Relational database management system and Combinatorics. His Data mining research incorporates themes from Real-time computing, Information retrieval and Task.

Between 2011 and 2020, his most popular works were:

• Generating and applying redo records (79 citations)
• Techniques for automatic data placement with compression and columnar storage (65 citations)
• Mirroring, in memory, data from disk to improve query performance (61 citations)

In his most recent research, the most cited papers focused on:

• Database
• Operating system
• Programming language

His scientific interests lie mostly in Database, Volatile memory, Bitstream format, Parallel computing and Database server. His study involves Database design, Database application, Database model, Database tuning and View, a branch of Database. His work on Matroska and Wireless Application Protocol Bitmap Format as part of his general Bitstream format study is frequently connected to Flash, Base and Cache, thereby bridging the divide between different branches of science.

His work in the fields of Parallel processing and SIMD overlaps with other areas such as Cluster and Fixed width. His biological study spans a wide range of topics, including Data placement, Computer graphics, Row and Column. His study in Online transaction processing is interdisciplinary in nature, drawing from both Object, Set and Relational database management system.