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On the Performance Impact of Data Access Middleware for NoSQL Data Stores
Abstract
The last few years have seen a drastic increase in the amount and the heterogeneity of
NoSQL data stores. Consequently, exploration and comparison of these data stores have become
difficult. Once chosen, it is hard to migrate to different data stores. Recently, a number of data
access middleware platforms for NoSQL have emerged that provide access to different NoSQL
data stores from standardized APIs. However, there are two key concerns related to: (i) the
performance overhead introduced by these platforms, and (ii) the effort required to migrate
between different data stores. In this paper, we present two complementary studies that provide
answers to the above mentioned concerns for three of the most mature data access middleware
platforms: Impetus Kundera, Playorm, and Spring Data. First, we evaluate the performance
overhead introduced by these platforms for the CRUD operations. Secondly, we compare the
cost of migration with and without these platforms. Our study shows that, despite their similarity
in design, these platforms are still substantially different performance-wise. Both studies are
complementary as they show the trade-off inherent in adopting a data access middleware
platform for NoSQL: by allowing some performance overhead, the developer gain benefits in
terms of portability and easy migration across heterogeneous data stores.
System Specification
System Requirements:
Hardware Requirements:

2. IEEE PROJECTS DEVELOPMENTS
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• System : Pentium IV 2.4 GHz.
• Hard Disk : 40 GB.
• Floppy Drive : 1.44 Mb.
• Monitor : 15 VGA Colour.
• Mouse : Logitech.
• Ram : 512 Mb.
Software Requirements:
• Operating system : - Windows 7. 32 bit
• Coding Language : C#.net 4.0
• Data Base : SQL Server 2008