hey guys on break and thinking about you guys

seen from United States

seen from Saudi Arabia
seen from Italy

seen from United States

seen from Saudi Arabia
seen from United Kingdom
seen from China
seen from Germany

seen from Netherlands
seen from Germany
seen from Russia
seen from Hungary
seen from Germany

seen from Netherlands
seen from Russia

seen from Türkiye

seen from United States

seen from Malaysia
seen from United States

seen from China
hey guys on break and thinking about you guys

Anya is live and ready to show you everything. Watch her strip, dance, and perform exclusive shows just for you. Interact in real-time and make your fantasies come true.
Free to watch • No registration required • HD streaming
BIOS Konfiguration (Set 2)
Motherboard: Gigabyte Aorus Z390 Pro
Aktualisierung des Bios: F12
Verwendung: Bootloader Open Core für OSX 11.2.3 (BS)
Screens 11-15
ak, 27.4.2020
Open Source or Open Core?
Writing for SiliconAngle, Jeffrey Kelly explores the pros and cons of Open Source v Open Core through the lens of two Hadoop companies. HortonWorks is squarely in the open source camp, whilst Cloudera follows the open core path by extending Hadoop's open source heart with proprietary twiddles.
As Jeff notes, the lead granted by being able to focus effort and attention on developing specific proprietary features can be strong but may prove short-lived; the broader community is bigger, and will eventually catch up. On the other hand, the pure open source company actually needs pretty deep pockets to support its growth in the months or years before revenue-generating business materialises. Grand partnerships are great, but rarely translate quickly into significant sums of cash.
It's easy to wax philosophical about the ultimate victory of the commons and all that... but the reality today is that Cloudera has more money ($141 million since 2009, to HortonWorks' $98 million since 2011) and more visibility.
Cloudera's burn rate may also be higher... but that visibility is probably translating into paid engagements as companies scrabble to big data-ify their own products and workflows.