Examples of using Relational data in English and their translations into Chinese
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Relational data warehouses served communications service providers well in the past, but it's time to start thinking beyond columns and rows.
To access other relational data sources, BigInsights provides a generic JDBC connector.
Previously structured relational data could not be analytically mixed and matched with unstructured textual data. .
This is a fairly common big data architecture, where a much smaller relational data warehouse is used to augment a Hadoop-based system.
In addition to these basic components, Hadoop also includes Sqoop, which moves relational data into HDFS;
Further, 35 percent say unstructured information has already surpassed or will surpass traditional relational data in the next 36 months.
A data warehouse is a database optimized to analyze relational data coming from transactional systems and line-of-business applications.
In a relational data model, it is often defined like a standard(virtual) view: a table-like object whose contents are the results of some query.
We offer a full suite of industry-leading storage services that are price performant and meet your needs for structured, unstructured, transactional, and relational data.
How do we collect not just biological data but behavioral data, psychological data, relational data, in and on and around the home?
For some time, Microsoft had promoted OLE DB as a better alternative for relational data access, so this could appear to some as backpedaling.
Relational Data Model Formalities.
Structured Data: These are relational data.
Object- Relational Data Management Systems.
The reason is relational data.
Drizzle can still store relational data;
This is relational data, not spatial data. .
Your environment is driven by relational data model.
MapReduce-Merge: Simplified relational data processing on large clusters.