Rental market snapshot for Kemah, Texas

Kemah, Texas Rental Property Market Overview

The average rent for an apartment in Kemah is $1,786. The cost of rent varies depending on several factors, including location, size, and quality.

The average rent has decreased by -5.7% over the past year.

Kemah is a city in Galveston County, Texas, United States, with a population of 2,330 at the 2010 census. The city is the home of Boardwalk FantaSea, a large yacht-themed restaurant and entertainment complex on Galveston Bay.

Last Updated December 23, 2022

Get updates straight to your inbox

Whenever this data is updated, you'll be the first to know. Don't miss out on crucial market insights.

Sign up

Average monthly rent graph in Kemah Texas | Cost of Living

  • The most expensive ZIP Code in Kemah is 77565 with an average price of $1,990
  • The cheapest ZIP Code in Kemah is 77565 with an average price of $1,960

Kemah ZIP Codes with the highest, most expensive rent

#zip codeaverage rent
177565$1,990

Live near Kemah, Texas's Top Sights and Attractions

Cien Park is an amusement park located in Kemah, Texas. The park features a variety of rides, including a Ferris wheel, a roller coaster, and a carousel. There is also a food court and a gift shop.

Kemah, Texas area median rent change by ZIP Code map

Get updates straight to your inbox

Whenever this data is updated, you'll be the first to know. Don't miss out on crucial market insights.

Sign up

How does Kemah compare to other cities in Texas ?

citymedian price
Mcallen$1,299
Krum$2,085
Missouri City$1,750
Hutto$2,065
Seagoville$2,045
Highlands$1,840
Roman Forest$1,675
Cedar Creek$1,795

Average household income in Kemah area graph - US Census

Get updates straight to your inbox

Whenever this data is updated, you'll be the first to know. Don't miss out on crucial market insights.

Sign up

The median household income in Kemah in 2021 was $100,294. This represents a 51.0% change from 2011 when the median was $66,429.

#categorypercent
0Less than $10,0001.4%
1$10,000 to $14,9994.9%
2$15,000 to $19,9991.5%
3$20,000 to $24,9991.2%
4$25,000 to $29,9995.0%
5$30,000 to $34,9992.2%
6$35,000 to $39,9993.1%
7$40,000 to $44,9993.2%
8$45,000 to $49,9992.6%
9$50,000 to $59,9996.7%
10$60,000 to $74,9999.0%
11$75,000 to $99,9999.0%
12$100,000 to $124,99911.2%
13$125,000 to $149,99921.1%
14$150,000 to $199,99910.4%
15$200,000 or more7.6%

Explore other rental market trend reports

Tile picture
Rents in Texas City, Texas
Tile picture
Rents in League City, Texas
Tile picture
Rents in Dickinson, Texas
Tile picture
Rents in Bacliff, Texas
Tile picture
Rents in Webster, Texas
Tile picture
Rents in Seabrook, Texas

Frequently asked questions

Our data is best categorized as "alternative data", which is a burgeoning sector. Through partnerships and direct feeds, we extract key factual elements that are publicly available within rental listings on internet listing sites and property websites. Once aggregated, we mine through the data to parse out relevant insights and calculate important metrics, benchmarks, and other KPIs. Each week, our system sifts through millions of listing observations and other pockets of market information to deliver the most comprehensive picture of rental housing available.

This is a metric that we try not to overthink. Simply, we take each unique listing observation within a geographic boundary and calculate a simple average. Of course, we're careful to filter for duplicates and other listings that aren't reflective of the market.

Yes, but please attribute us accordingly.

Yes. We can deliver bulk raw data in various formats. Please contact us to discuss - [email protected]

While some of our data is refreshed daily and other data comes in weekly, the bulk of it comes in on a biweekly basis.

Our coverage is nationwide! In our platform, we have data points for every ZIP code and neighborhood boundary in the country.

Every rental housing unit is differentiated by attributes such as its location, square footage, and amenity composition. Thanks to machine learning and natural language processing technologies we deploy, we're able to deconstruct our rental listing data points and identify key amenities for each listing. With this information, we're able to give signals around how certain amenities drive rental pricing value in certain areas.

Well, we think so! At the highest level, our process is simple. Listings data is ingested, cleaned (de-duplicated. etc.), analyzed for insights, and then presented to our users.
Made withDataherald