This paper introduces RUKA, a newly designed open-source, low-cost, and anthropomorphic robotic hand intended for research in dexterous manipulation. It details RUKA's hardware design, emphasizing its tendon-driven actuation, 3D-printed components, and off-the-shelf parts, achieving a balance of precision, durability, and affordability. The paper further presents a data-driven control approach utilizing motion capture gloves for teleoperation and policy learning, demonstrating RUKA's capabilities through various reachability, strength, and durability tests, outperforming existing robotic hands in several metrics. Finally, it explores applications of RUKA in teleoperation and imitation learning, highlighting its potential as an accessible platform for advancing robotic dexterity.