Self-configuring adapter

1. A method comprising:

receiving, using one or more processors, a query in a relational query language;

obtaining, using the one or more processors, via a first application programming interface (API), an API result set from a first endpoint based on the query in the relational query language;

determining, using the one or more processors, a relational result set responsive to the query in the relational query language based on an extrapolation from a sample set of results received from the first endpoint and a set of rules, wherein the sample set of results is distinct from the API result set and received responsive to a sampling distinct from the received query in the relational query language, wherein an initial set of data types and an initial relational data structure are extrapolated as an initial relational data structure representing data stored by the first endpoint and exposed via the first API, wherein the sample set of results is a subset comprising less than an entirety of data exposed by the first endpoint via the first API; and

sending, using the one or more processors, the relational result set responsive to the query in the relational query language.

2. The method of claim 1 further comprising:

receiving, from the first endpoint and responsive to the sampling of the first endpoint, the sample set of results; and

extrapolating, based on the sample set of results received from the first endpoint and based on the set of rules, the initial set of data types and the initial relational data structure, wherein the data stored by the first endpoint and exposed via the first API includes a complex data type, and wherein the initial relational data structure including a relational representation of the complex data type.

3. The method of claim 2 , wherein the sampling and automatic extrapolation are repeated on a per-session basis and responsive to an initiation of a session.

4. The method of claim 1 , wherein the initial set of extrapolated data types and initial relational data structure representing the data stored by the first endpoint and exposed via the first API are merged with a second set of extrapolated data types and a second relational data structure representing data stored by a second endpoint.

5. The method of claim 4 , wherein the second endpoint is exposed via a second API, and the first API and second API differ.

6. The method of claim 1 further comprising:

obtaining user input requesting modification of the relational data structure representing the data stored by the first endpoint and exposed via the first API; and

generating a new relational data structure representing the data stored by the first endpoint and exposed via the first API based on the requested modification.

7. The method of claim 6 , wherein the user input requesting modification is a request to modify one or more of a data type, data structure, and normalization type.

8. The method of claim 1 , wherein the sample set of results represent most recent data of the first endpoint.

9. The method of claim 1 further comprising:

updating the relational data structure representing the data stored by the first endpoint and exposed via the first API responsive to one or more of a user-initiated request and automatically based on satisfaction of a criterion.

10. The method of claim 1 further comprising:

mapping the query in the relational query language to one or more first API queries based on the relational data structure representing the data stored by the first endpoint and exposed via the first API, the one or more API queries including a first API query, the first API query using the first API and sent to the first endpoint.

11. A system comprising:

one or more processors; and

a memory storing instructions that, when executed by the one or more processors, cause the system to:

receive a query in a relational query language;

obtain, via a first application programming interface (API), an API result set from a first endpoint based on the query in the relational query language;

determine a relational result set responsive to the query in the relational query language based on an extrapolation from a sample set of results received from the first endpoint and a set of rules, wherein the sample set of results is distinct from the API result set and received responsive to a sampling distinct from the received query in the relational query language, wherein an initial set of data types and an initial relational data structure are extrapolated as an initial relational data structure representing data stored by the first endpoint and exposed via the first API, wherein the sample set of results is a subset comprising less than an entirety of data exposed by the first endpoint via the first API; and

send the relational result set responsive to the query in the relational query language.

12. The system of claim 11 comprising instructions that, when executed by the one or more processors, cause the system to:

receive, from the first endpoint and responsive to the sampling of the first endpoint, the sample set of results; and

extrapolate, based on the sample set of results received from the first endpoint and based on the set of rules, the initial set of data types and the initial relational data structure, wherein the data stored by the first endpoint and exposed via the first API includes a complex data type, and wherein the initial relational data structure including a relational representation of the complex data type.

13. The system of claim 12 , wherein the sampling and automatic extrapolation are repeated on a per-session basis and responsive to an initiation of a session.

14. The system of claim 11 , wherein the initial set of extrapolated data types and initial relational data structure representing the data stored by the first endpoint and exposed via the first API are merged with a second set of extrapolated data types and a second relational data structure representing data stored by a second endpoint.

15. The system of claim 14 , wherein the second endpoint is exposed via a second API, and the first API and second API differ.

16. The system of claim 11 comprising instructions that, when executed by the one or more processors, cause the system to:

obtain user input requesting modification; and

generate a new relational data structure representing the data stored by the first endpoint and exposed via the first API based on the requested modification.

17. The system of claim 16 , wherein the user input requesting modification is a request to modify one or more of a data type, data structure, and normalization type.

18. The system of claim 11 , wherein the sample set of results represent most recent data of the first endpoint.

19. The system of claim 11 comprising instructions that, when executed by the one or more processors, cause the system to:

update the relational data structure representing the data stored by the first endpoint and exposed via the first API responsive to one or more of a user-initiated request and automatically based on satisfaction of a criterion.

20. The system of claim 11 comprising instructions that, when executed by the one or more processors, cause the system to:

map the query in the relational query language to one or more API queries based on the relational data structure representing the data stored by the first endpoint and exposed via the first API, the one or more API queries including a first API query, the first API query using the first API and sent to the first endpoint.