Abstract
Traditionally, data was in text format and generally accessed using JDBC adapters from an RDBMS. Unstructured data like documents were accessed from document management systems (DMS) using simple HTTP calls. For performance, improvement concepts like caching were implemented. In the big data world, because the volume of data is too huge (terabytes and upwards), traditional methods can take too long to fetch data. This chapter discusses various patterns that can be used to access data efficiently, improve performance, reduce the development lifecycle, and ensure low-maintenance post-production.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2013 Nitin Sawant
About this chapter
Cite this chapter
Sawant, N., Shah, H. (2013). Big Data Access Patterns. In: Big Data Application Architecture Q & A. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4302-6293-0_5
Download citation
DOI: https://doi.org/10.1007/978-1-4302-6293-0_5
Published:
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4302-6292-3
Online ISBN: 978-1-4302-6293-0
eBook Packages: Professional and Applied ComputingApress Access BooksProfessional and Applied Computing (R0)