Datasheet: SQL Server 2016
By: Microsoft View more from Microsoft >>
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Why NoSQL for AI-powered applications: An architectural guide
By: Couchbase
Type: White Paper
NoSQL is a modern database management system that stores information in JSON documents instead of the tables, columns, and rows used by relational databases. NoSQL databases are built to be flexible, scalable, and capable of rapidly responding to the data management demands of modern businesses, which means they can serve as the basis for AI applications that need ultimate adaptability now and into the future.
In this Architectural Guide you will learn:
- The differences and similarities between NoSQL and relational databases
- How NoSQL supports SQL developers with added flexibility
- 5 key technology trends where NoSQL outperforms relational
- Why NoSQL is a better fit for large-scale requirements
These are also closely related to: "Datasheet: SQL Server 2016"
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CW APAC: Trend Watch: Database technology
By: TechTarget ComputerWeekly.com
Type: Ezine
Innovative data management offerings are improving the efficiency of enterprise operations. In this handbook, focused on database technology in the Asia-Pacific region, Computer Weekly looks at the impact of graph databases, Neo4j’s partnership with Deloitte, TigerGraph’s added security features and the different types of database management systems currently on the market.
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Data integration to support modern BI and advanced analytics programmes
By: TechTarget ComputerWeekly.com
Type: eGuide
Data integration and preparation are the unsung heroes of modern BI and advanced analytics. More so than ever, it would seem, due to the ever-increasing volume and variety of data.
The traditional paradigm of feeding a data warehouse with data that had been extracted from source systems, including transactional databases, then transformed to be loaded for subsequent analysis, using BI tools or statistical analysis software – that paradigm is not History, but it is being complemented with newer models. These latter are more about analysing real-time data, using fast, in-memory databases on the back end. And there is a raft of data preparation tools now available to get the data spruced up and ready for analysis quicker.
Some of these tools have come out of Silicon Valley, where much of the relatively recent wave of back end big data technologies, too, have been invented – originally to serve the needs of Google, Facebook, Amazon, and the rest. We look at some of these data integration and preparation technologies, as show-cased on press trips to Silicon Valley. The most recent of these brought to the fore the need for CIOs to get more economic value from their investments in big data technologies through data integration, including data catalogues.
Dave Wells, practice director, data management at the Eckerson Group puts these more recent approaches in perspective, in a spirited blogpost that argues that the “traditional” data warehouse is not dead.
We also look, in this e-guide, at how British Airways has brought its international business-to-business sales under Salesforce Sales Cloud to bust its data silos. The self-service BI that BA is enabling for its sales professionals is an ambition for many companies. Consultant Rick Sherman, in an interview with SearchDataManagement’s Jack Vaughan, explains how understanding the data integration process is central to such self-service BI and data architecture design.
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Modern NoSQL databases incorporate multiple data access methods and encompass a variety of models including key-value, document, column, time series, graph, text search, and AI vector search. This developer’s guide explains the many advantages that are making multipurpose NoSQL databases the developer’s choice for AI-powered adaptive applications.
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Check out this white paper for a look inside the modern challenges that NoSQL databases address, as well as when to choose NoSQL over relational and why.
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