doppelganger1

6 ms·

1.
by doppelganger1 5y ago
Hadoop was built on the notion that commodity hardware, when pooled together, can be extremely cheap and powerful. The problem is, to manage it, is a nightmare. Cloudera/HWX and others were unable to reduce the management burden and th
2.
by doppelganger1 5y ago
Actually, you would expect that in an OLTP world. DW's for the longest time, even Oracle, recommends you disable txn to get better performance. The logic is implemented in the ETL layer. Very rarely do you need multi-table txn in large
3.
by doppelganger1 5y ago
What about my comment above is pro-Databricks? Snowflake works the same way. So do most large scale DW insert Exadata, Netezza, etc... Does anyone else notice people questioning common sense?
4.
by doppelganger1 5y ago
Also, if a sales rep or manager are struggling to make their numbers, they will audit customers.
5.
by doppelganger1 5y ago
What I find comical is they accuse Databricks of lacking integrity but they don’t actually call out anything except their benchmark was faster than what Databricks did in Snowflake. Databricks then reruns the benchmark and says the only rea
6.
by doppelganger1 5y ago
Have you ever tried to train models on large data sets over JDBC/ODBC? it’s terrible even with parallelism. Having direct access to the underlying storage and being able to bypass sucking a lot of data over a small straw is a game chan
7.
by doppelganger1 5y ago
Big Query&Data Proc, Redshift&EMR, Synapse&HDR are tied to the cloud vendors. You can’t move easily from AWS stack to GCP without refactoring. Switching costs are higher. Snowflake and Databricks are multicloud. The different is
8.
by doppelganger1 5y ago
SF spreads a lot of FUD saying that DB can’t perform, and it was true. DB then went out and hired a lot of engineering talent with a diverse background and has been investing a lot of money in being a best in class SQL offering, so what do
9.
by doppelganger1 5y ago
The first thing unbreakable Linux did was break.
10.
by doppelganger1 5y ago
Oracle Exadata is very fast but expensive. I bet it would beat a similarly sized cluster from these 2 vendors. The problem is price to performance and elasticity. Because DB and SF are in the cloud, they have a lot more options that Oracle
11.
by doppelganger1 5y ago
The larger your data, the more that indexing and maintaining them hurt you. This is why they do much better at larger datasets vs small data sets. It’s all about trade offs. To overcome this, they make use of cache and if the small data is