Build a Python program that scrapes the titles and URLs of the top 10 trending GitHub repositories from https://github.com/trending and saves them to a SQLite database.

First, you need to install the required libraries. You can do this by running:

```bash
pip install requests beautifulsoup4
```

Now, let's create a Python script that scrapes the top 10 trending GitHub repositories and saves them to an SQLite database.

```python
import requests
from bs4 import BeautifulSoup
import sqlite3

# Fetch the content of the GitHub Trending page
url = "https://github.com/trending"
response = requests.get(url)
content = response.content

# Parse the HTML content using Beautiful Soup
soup = BeautifulSoup(content, "html.parser")

# Find the top 10 repository elements
repo_elements = soup.find_all("h1", class_="h3 lh-condensed")[:10]

# Extract the titles and URLs of the repositories
repos = []
for repo in repo_elements:
    title = repo.text.strip().replace("\n", "").replace(" ", "")
    url = "https://github.com" + repo.find("a")["href"]
    repos.append((title, url))

# Create an SQLite database and save the data
conn = sqlite3.connect("trending_repos.db")
cursor = conn.cursor()

# Create the table if it doesn't exist
cursor.execute("""
CREATE TABLE IF NOT EXISTS trending_repos (
    id INTEGER PRIMARY KEY AUTOINCREMENT,
    title TEXT NOT NULL,
    url TEXT NOT NULL
)
""")

# Insert the scraped data into the table
cursor.executemany("""
INSERT INTO trending_repos (title, url) VALUES (?, ?)
""", repos)

# Commit the changes and close the connection
conn.commit()
conn.close()

print("Top 10 trending GitHub repositories have been saved to the SQLite database.")
```

This script will scrape the top 10 trending GitHub repositories from https://github.com/trending and save their titles and URLs to an SQLite database named `trending_repos.db`. You can run this script using Python 3:

```bash
python scrape_github_trending.py
```

After running the script, you should see a message indicating that the data has been saved to the SQLite database.