PHPMem v2.0.1

Version
1.6.45
Uptime
16 days 21 hours 59 minutes 29 seconds

Memory

Total
512MB
Used
12,72MB (2.48%)
Free
499,28MB

Keys

Current
14 060
Total (since start)
40 994
Evictions
0
Reclaimed
760
Expired Unfetched
0
Evicted Unfetched
0

Connections

Current
14 / 1 024 max
Total
192 687
Rejected
0
llm:ca82a5543b419ce4764b2f0e5f5ef2bfcfee464a368cb74fe7164c986e76865b
TTL 6 days 5 hours 17 minutes 54 seconds Size 1,93KB Export
Edit
**The most counterintuitive finding is how concentrated the money is: the "typical" Indian startup deal and the dollar total tell completely different stories.** - Of 3,044 rows, 2,065 have a usable USD amount (SQL in step 15). The other 979, about a third, have no amount. - Total disclosed funding is about **$38.06B**, but the **median deal is only $1.7M**. The mean is about $18.4M, roughly 10x the median. - Only **73 deals of $100M or more** (about 3.5% of valued deals) account for **63.6% of all dollars**. - The single largest deal is **Rapido Bike Taxi, a "Series B" dated 27/08/2019, at $3.9B**. That alone is about **10.2%** of all disclosed dollars. It is larger than Flipkart's $2.5B private-equity round in 2017 (step 0). The Rapido figure is suspicious. A Series B larger than the biggest Flipkart and Paytm rounds looks more like a unit or entry error than a real deal. That is my reading, not something the data confirms. If it is an error, the total and the share held by large deals would both shift noticeably. **What the evidence leaves open** - **Amount parsing:** Some of my queries returned `nan` for totals and maxima, and step 8 flagged one non-finite amount row. The Drums Food row (21/07/2016) has a non-numeric amount and sorts to the top of rankings. The step-15 figures exclude it, and I did not check what its raw text says. - **Missing amounts:** I did not test whether the 979 unvalued rows differ systematically, for example by round type or year. If large deals are disclosed more often than small ones, the median would be even lower than reported. - **Other checks:** I did not run any breakdown by year, city, vertical or investor, or any duplicate check (for example, Flipkart and Flipkart.com appear as separate names). So I cannot say whether the concentration is driven by a few sectors or periods.