Kipling Womens Delia Mini Backpack vs Baggallini Back To Basics Backpack

The main difference between the Kipling Womens Delia Mini Backpack and the Baggallini Back To Basics Backpack is that the Womens Delia Mini Backpack has Side Pockets (Side pockets can fit water bottle) while the Back To Basics Backpack does not.

Kipling Womens Delia Mini Backpack Front View
Baggallini Back To Basics Backpack - Front View
Specs Brand Kipling Baggallini
Name Womens Delia Mini Backpack Back To Basics Backpack
Category Womens Mini
Sub Category Mini Womens
Capacity (L) 8L
Dimensions (in) 8.75 x 7 x 11.5 9.5 x 11 x 2
Weight (lb) 0.8 1
Fabric 100% Polyamide
Color 4 Colors and patterns Blush Python
Warranty Kipling Limited Warranty
Rating 4.2
Price Under $125 Under $100
General Features Shoulder Straps Adjustable shoulder straps Adjustable backpack straps, straps convert from backpack to sling
Water Proof / Water Resistant Water resistant crinkle nylon Water resistant
Zippers Nylon zipper with metal pulls
Main Compartment Access Normal zipped access Normal top zip access
External Pockets 2 zipped front pocket and 2 side pockets 2 external pockets
Internal Compartments Inside zipped pocket Interior organization and multifunctional pockets
Side Pockets Side pockets can fit water bottle
Water Bottle Yes
Handles Top grab handle Top grab handle
Lightweight Lightweight
Hiking / Backpacking Features Back Panel Padded

You're currently comparing the Womens Delia Mini Backpack by Kipling against the Back To Basics Backpack by Baggallini .


Kipling 's Womens Delia Mini Backpack is a Womens backpack with Mini features while Baggallini 's Back To Basics Backpack is a Mini backpack with Womens features.

The Kipling Womens Delia Mini Backpack has a capacity of 8L (liters), weighs 0.8 pounds and it's dimensions in inches are 8.75 x 7 x 11.5. It's made of 100% Polyamide and is available in 4 Colors and patterns in comparison the Baggallini Back To Basics Backpack's capacity is with a size of 9.5 x 11 x 2 inches. Constructed from it weighs 1 pounds and is available in Blush Python.