From zero to useful
in minutes.
Familiar SQL on the surface. A watchful operating layer underneath. Here is how FlyDB is designed to fit into your workflow.
flydb create customer-appThese examples show how FlyDB moves from setup to insight and safe optimization.
One database.
Ready to connect.
Create a database near your users, then receive a familiar PostgreSQL connection string for your application.
$ flydb create customer-app --region us-east
✓ Database ready in the United States
postgres://flydb••••@us-east.flydb.dev/customer-app
$ flydb connect customer-app
✓ Connected · TLS enabledBring the SQL
you already know.
FlyDB is designed around familiar relational workflows. Create tables, change data, and query it with straightforward SQLite.
CREATE TABLE projects (
id INTEGER PRIMARY KEY,
name TEXT NOT NULL,
status TEXT NOT NULL,
language TEXT NOT NULL
);
SELECT name, status, language
FROM projects
ORDER BY name;Ask what changed.
Get the evidence.
Use ordinary language when you need an explanation. FlyDB shows its reasoning and the SQL behind the answer.
The orders endpoint began scanning more rows as the api_requests table grew. Overall traffic remained within its normal range.
- EvidenceSequential scan appeared at 10:22
- Affected queryrecent_endpoint_requests
- Likely fixIndex endpoint + created time
See diagnostic SQL
EXPLAIN QUERY PLAN
SELECT * FROM api_requests
WHERE endpoint = '/v1/orders'
ORDER BY created_at DESC;Know the impact
before the change.
FlyDB proposes a bounded action, explains its value, and prepares the rollback. You decide when it moves.
Speed up request history
CREATE INDEX IF NOT EXISTS
idx_requests_endpoint_created
ON api_requests (endpoint, created_at);Useful by default.
Understandable by design.
01Familiar SQL↗
02Explainable recommendations↗
03Guarded automation↗
04Reversible operations↗
05Visible costs↗
