BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//pretalx//programme.europython.eu//europython-2023//speaker//3CXHP
 7
BEGIN:VTIMEZONE
TZID:CET
BEGIN:STANDARD
DTSTART:20001029T040000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10
TZNAME:CET
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
END:STANDARD
BEGIN:DAYLIGHT
DTSTART:20000326T030000
RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3
TZNAME:CEST
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
UID:pretalx-europython-2023-EWHVWK@programme.europython.eu
DTSTART;TZID=CET:20230719T121000
DTEND;TZID=CET:20230719T124000
DESCRIPTION:Currently\, SQL and Cloud Data Warehouses (DWH) are extremely p
 opular for good reason. They are great for dashboarding and business intel
 ligence (BI) use cases due to their ease-of-use. However\, their combinati
 on might not be the best choice for every problem. More precisely\, busine
 ss-critical data pipelines with high complexity might be better suited for
  frameworks such as Apache Spark which greatly benefit from the tight inte
 gration with general purpose languages like Python (e.g.\, PySpark). \n\nE
 xpect an opinionated comparison between Apache Spark and seemingly easier-
 to-use cloud native SQL engines. By the end of this talk\, you will be cha
 llenged to think about why they are complementary and when each has its ju
 stification.
DTSTAMP:20260418T100632Z
LOCATION:North Hall
SUMMARY:Apache Spark vs cloud-native SQL engines - Franz Wöllert
URL:https://programme.europython.eu/europython-2023/talk/EWHVWK/
END:VEVENT
END:VCALENDAR