InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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What is CouchDB and Why Should I Care?
CouchDB, a NoSQL solution, is a document-oriented database and within each document fields are stored as key-value maps. CouchDB has some unique characteristics like advanced replication. This article covers getting started, unit testing, CRUD and query operations.
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Virtual Panel: NoSQL Database Patterns and Polyglot Persistence
NoSQL database space has different databases that support different data storage patterns. InfoQ spoke with four panelists about the current state of NoSQL adoption, architecture patterns supported by different NoSQL databases, polyglot persistence and security aspects when using NoSQL databases.
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Implementing Aggregation Functions in MongoDB
In this article, authors Arun Viswanathan and Shruthi Kumar discuss how to implement common aggregation functions on a MongoDB document database using its MapReduce functionality. They also discuss a typical application of aggregations which includes business reporting of sales data.
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Data Modeling: Sample E-Commerce System with MongoDB
The rich document capabilities and atomic operation guarantees in MongoDB makes it possible to model many different applications. Even rigorous requirements of conventional applications like e-commerce system are possible in a document database. This data model (i.e. "schema design,") is useful for developing applications around any restricted resource system, not just e-commerce systems.
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CAP Twelve Years Later: How the "Rules" Have Changed
The CAP theorem asserts that any networked shared-data system can have only two of three desirable properties (Consistency, Availability and Partition Tolerance). In this IEEE article, author Eric Brewer discusses how designers can optimize consistency and availability by explicitly handling partitions, thereby achieving some trade-off of all three.
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Introduction to MongoDB for Java, PHP and Python Developers
The NoSQL movement is here to stay. The need for reliable storage that can be easily queried and easily scalable without the pain of SQL schema migration is real. Developers want more agile systems. This article uses MongoDB to introduce NoSQL concepts. This article covers the basics of MongoDB architecture, caveats and programming in MongoDB for Java, PHP, and Python developers.
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MongoDB, Java and Object Relational Mapping
Brian C. Dilley covers pitfalls, & strengths of using MongoDB ("a very approachable NoSQL solution"), and introduces MJORM. The MJORM project is an annotation free MongoDB Java ORM library. This article builds on Brian's real world in the trenches experience with MongoDB and includes "gotchas" like "Don't treat MongoDB like an RDBMS...", how to "design your indexes carefully", and more.
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Evolution in Data Integration From EII to Big Data
With the emergence of inexpensive cloud-based storage and cost-effective ways to process large volumes and complex data there has been a shift in approach toward data integration.
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Implementing Lucene Spatial Support
Lucene geospatial extension proposed in this article is based on a two level search – first level search is based on Cartesian Grid search and the second level implements shape specific spatial calculations
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Exploring Hadoop OutputFormat
As more companies adopt Hadoop, its integration with other applications is becoming more important. A key to such integration is usage of the appropriate OutputFormat allowing to produce output data in a form most appropriate for other applications.
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Virtual Panel: Security Considerations in Accessing NoSQL Databases
NoSQL databases offer alternative data storage options for storing unstructured data compared to traditional relational databases. Though the NoSQL databases have been getting a lot of attention lately, the security aspects of storing and accessing NoSQL data haven't been given much emphasis. This article focuses on the security considerations and best practices in accessing the NoSQL databases.
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Uncovering mysteries of InputFormat: Providing better control for your Map Reduce execution.
In their article authors, Boris Lublinsky and Mike Segel, show how to leverage custom InputFormat class implementation to tighter control execution strategy of Maps in Hadoop Map Reduce jobs.