vgt

34 ms·

1. 331.▲
   by vgt 10y ago

   Aw well here ya go then! https://cloud.google.com/docs/compare/aws/
2. 332.▲
   by vgt 10y ago

   Are you talking about the Cloud ML service that was in private Alpha? Would love to hear if your opinion has changed now that it's Beta. Alpha products tend to have rough edges all around. (work at GCP)
3. 333.▲
   Google Cloud Machine Learning: now open to all(cloud.google.com)

   3 points by vgt 10y ago|0 comments
4. 334.▲
   BigQuery: introducing powerful new enterprise data warehousing features(cloud.google.com)

   1 points by vgt 10y ago|0 comments
5. 335.▲
   by vgt 10y ago

   This comes up sometimes, and is really not well supported. Happy to discuss every time it does come up :) Google Cloud is paid b2b, not free b2c - companies like Disney, Spotify, Evernote build very close multi-year relationships with Googl
6. 336.▲
   by vgt 10y ago

   I'm genuinely curious on what limitations you've seen with Google's Cloud. Google Compute Engine alone has lots of nifty features that even AWS EC2 lacks, like custom VMs, generalized VM types (no need to go for specific inst
7. 337.▲
   by vgt 10y ago

   Very timely: https://cloudplatform.googleblog.com/2016/09/global-historic...
8. 338.▲
   by vgt 10y ago

   > And not a single one of them has anything close to the wide and growing offering that AWS presents. I don't think that's an accurate statement. Google Cloud and Azure have broad offerings, and in many cases eclipse AWS (ex: B
9. 339.▲
   by vgt 10y ago

   Google Cloud has made several big efforts to make cloud pricing cheaper, simpler, and more flexible for its customers: - List Prices are cheaper [-1] - Google Sustained Use Discounts are like RIs but applied automatically and without commit
10. 340.▲
    by vgt 10y ago

    Let's note that the analysis was done on Google BigQuery's GitHub public dataset
11. 341.▲
    by vgt 10y ago

    I understand your points - it's narrative that's floating on the internet, and it's one that's very easy to believe. Unfortunately [2] is 100% opinion. As far as [1], every single "large" deal is negotiated. Th
12. 342.▲
    by vgt 10y ago

    I agree, of course. However, insinuating that such an announcement, and choice of cloud partnership, is dictated heavily by preferential pricing diminishes both customer's decision making and provider's intrinsic abilities. It&#x2
13. 343.▲
    by vgt 10y ago

    While I've heard this narrative discussed before, I'd like to offer some thoughts: - Companies do not (or should not) make cloud purchasing decisions be based entirely on some kind of preferential pricing. Cloud is far from a comm
14. 344.▲
    by vgt 10y ago

    True. And there's a paper for that: https://cloud.google.com/security/encryption-at-rest/ (work at GCP)
15. 345.▲
    by vgt 10y ago

    Pipelining helps with hanging chads, tail latency of work steps. If you have a slow worker (due to, say, data skew), entire job slows down. All other workers are sitting idle, waiting for the one worker to finish their piece. Read [0] to se
16. 346.▲
    by vgt 10y ago

    It's exciting to see new innovative open source contributions to the big data space. Since BigQuery has moved on in many ways from the ColumnIO and Dremel concepts described in the Dremel paper[0] with new versions of many of these com
17. 347.▲
    by vgt 10y ago

    While both Spark and BigQuery do the shuffle step in-memory, there are some differences[1]: - BigQuery's execution is pipelined (don't wait for step 1 to finish to start step 2) - BigQuery's in-memory shuffler is not co-tenan
18. 348.▲
    by vgt 10y ago

    Here is the video from Sungard FIS and Google Cloud discussing their approach: https://www.youtube.com/watch?v=fqOpaCS117Q TL;DR: They achieved a peak of 56m qps and sustained 38m qps when processing market data. (disc: I w
19. 349.▲
    by vgt 10y ago

    Congrats WagonHQ folks!
20. 350.▲
    by vgt 10y ago

    You are missing the part about customer's servers being used for malicious purposes (without their knowledge alas)
21. 351.▲
    Google BigQuery continues to define what it means to be fully managed(cloud.google.com)

    2 points by vgt 10y ago|0 comments
22. 352.▲
    by vgt 10y ago

    TL;DR: 1. Cloud Bigtable is GA [0] 2. Cloud Datastore GA [1] 3. Cloud SQL 2.0 GA [2] 4. Persistent Disk SSD now gets 25,000 IOPS [3] 5. SQL Server images available [3] 6. Custom Encryption Keys in Google Cloud Storage [3] 7. Google Nearline
23. 353.▲
    by vgt 10y ago

    Really excited to see the open source community around big data grow. Three minor points on "locked-in" and "too expensive": - BigQuery now has fully standard SQL and allows for easy exports of ALL your data out of BigQu
24. 354.▲
    by vgt 10y ago

    Here is the blog describing the Capacitor storage engine (successor to ColumnIO, which was the inspiration for Parquet): https://cloud.google.com/blog/big-data/2016/04/inside-capaci... Here's the bl
25. 355.▲
    Google BigQuery hits the gym to beef up even more(shinesolutions.com)

    3 points by vgt 10y ago|3 comments
26. 356.▲
    Azure vs. AWS vs. Google Cloud – Comparing SSDs(medium.com)

    7 points by vgt 10y ago|0 comments
27. 357.▲
    by vgt 10y ago

    12 weeks is 3 months :) I believe FB is 16 weeks?
28. 358.▲
    by vgt 10y ago

    Agreed. Lots of goodies announced, including taking Nearline Storage to near-realtime (versus 3+ hours on Glacier) and an increase in IOPS for some persistent disks.
29. 359.▲
    by vgt 10y ago

    Powered by SQLstream, which have been around since early 2000's: https://twitter.com/SQLstream/status/763826133401866240
30. 360.▲
    by vgt 10y ago

    Somewhat of a shameless plug (work at Google). While AWS has shown willingness to lower prices, they seem to have forfeited price leadership to Google Cloud. Examples: 1. http://fortune.com/2016/01/08/google-a