When can “big data” be “in-memory”?
| dc.contributor.author | Sedlar, Eric | |
| dc.contributor.editor | Seidl, Thomas | |
| dc.contributor.editor | Ritter, Norbert | |
| dc.contributor.editor | Schöning, Harald | |
| dc.contributor.editor | Sattler, Kai-Uwe | |
| dc.contributor.editor | Härder, Theo | |
| dc.contributor.editor | Friedrich, Steffen | |
| dc.contributor.editor | Wingerath, Wolfram | |
| dc.date.accessioned | 2017-06-30T11:40:46Z | |
| dc.date.available | 2017-06-30T11:40:46Z | |
| dc.date.issued | 2015 | |
| dc.description.abstract | The monikers of “big data” and “in-memory” are certainly hyped in the database world, but some people might argue that they don't overlap. The terms are vague enough to be treated as mutually exclusive as well as mostly overlapping. In addition, “big data” often implies “data science” which means “not SQL” (based on some programmable framework like Map-Reduce, Spark, or Flink). How do we see the “in-memory” and “big data” trends for analytics evolving in the future (separately or together) and what is the role of SQL vs. | en |
| dc.identifier.isbn | 978-3-88579-635-0 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Datenbanksysteme für Business, Technologie und Web (BTW 2015) | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-241 | |
| dc.title | When can “big data” be “in-memory”? | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 25 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 25 | |
| gi.conference.date | 2.-3. März 2015 | |
| gi.conference.location | Hamburg |
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