PHPMem v2.0.1
Version
1.6.45
Uptime
16 days 23 hours 58 minutes 25 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
15 / 1 024 max
Total
193 816
Rejected
0
llm:e214fdf03e738dc27530d1ffff51a87f34a1bc7640bbd0c71088fe53b4c0e440
Edit
**The most important numeric metric is `Amount in USD`, the reported size of each funding deal.** It is the only true measure in the dataset (the card lists it as the sole measure). It is stored as text, with Indian-style digit grouping such as `3,90,00,00,000`, and was parsed into a number for the queries.
**Highest records (largest deals)**
- **Rapido Bike Taxi** has the largest deal: a Series B on 27/08/2019 in Bengaluru, at **$3.9 billion** (`3,90,00,00,000`).
- **Flipkart** is next with a Private Equity round on 11/08/2017 in Bangalore at **$2.5 billion**.
- **Flipkart** (21/03/2017) and **Paytm** (18/05/2017) tie at **$1.4 billion**, both Private Equity in Bangalore.
- **Paytm** raised $1.0 billion in a Funding Round in Noida on 25/11/2019.
- The rest of the top 10 run from $700M (Flipkart.com, 2015) down to $585M (Udaan, Series D, 2019).
Private Equity dominates the top of the ranking, and Flipkart and Paytm appear repeatedly.
**Lowest records (smallest deals)**
- The smallest reported amount is **$16,000**. Five Seed Funding deals on 19/01/2015 share it: Hostel Dunia, Play your sport, Yo Grad, CBS and Enabli. None of them has a city recorded.
- The next smallest is **$16,600**, shared by several Seed deals on 02/02/2015, including Dealwithus, Leaf, Faaya and InstaBounce. Their round type is stored as `Seed\nFunding`, a stray newline.
**Caveats**
- **Missing amounts:** Some rows have no amount. For example, *Drums Food* (21/07/2016, Mumbai) appeared first in an early highest-first sort, but its amount is null, so it is not a real top deal. I excluded it from the rankings above.
- **Skew:** The spread from $16K to $3.9B is about five orders of magnitude, so averages will be dominated by a handful of mega-deals. Use medians or per-round benchmarks instead.
- **Minimum may be a reporting floor:** The lowest values cluster at the start of the data (January–February 2015). This may reflect how amounts were reported then rather than genuinely tiny deals.
- **Messy text fields:** Labels are inconsistent (Bangalore vs Bengaluru, eCommerce vs ECommerce, the newline in `Seed\nFunding`). Clean these before grouping by city, vertical or round.