docs: migrate from memmap to sqlite

[alaeddine-13]

docs: migrate from memmap to sqlite

[github-actions]

Latency summary

Current PR yields:

• 🐢🐢 index QPS at 860, delta to last 2 avg.: -28%
• 😶 query QPS at 36, delta to last 2 avg.: -1%
• 🐎🐎🐎🐎 avg flow time within 2.2014 seconds, delta to last 2 avg.: +46%
• 😶 import jina within 0.4382 seconds, delta to last 2 avg.: +5%

Breakdown

Version	Index QPS	Query QPS	Avg Flow Time (s)	Import Time (s)
current	860	36	2.2014	0.4382
2.7.0	1209	51	1.4446	0.3509
2.6.4	1181	21	1.5656	0.4773

Backed by latency-tracking. Further commits will update this comment.

[JohannesMessner]

I am worried that this does not really fit the purpose of the migration guide, which really just tells people what they need to do to get their code working with Jina 3, as succinctly as possible. For further explanations it should refer to external resources. As you can see, document stores would be by far the longest item here.

So I suggest the following compromise:

Suggested change

	### DocumentArray: new storage options
	Jina 2 used to offer persistence of DocumentArray through `DocumentArrayMemmap`. In Jina 3, this data structure is
	deprecated and we introduce different [Document Stores](https://docarray.jina.ai/advanced/document-store/) within the
	`DocumentArray` API. Thus, you can enjoy a consistent `DocumentArray` API across different storage backends and leverage
	modern databases.
	For example, you can use [SQLite backend](https://docarray.jina.ai/advanced/document-store/sqlite/) as a replacement
	for `DocumentArrayMemmap`:
	```python
	from docarray import Document, DocumentArray
	das = DocumentArray(storage='sqlite', config={'connection': 'my_connection', 'table_name': 'my_table_name'})
	das.extend([Document() for _ in range(10)])
	```
	This will persist the Documents into disk using SQLite and therefore, you should find the Documents within another
	session:
	```python
	from docarray import DocumentArray
	das = DocumentArray(storage='sqlite', config={'connection': 'my_connection', 'table_name': 'my_table_name'})
	das.summary()
	```
	```text
	Documents Summary
	Length 10
	Homogenous Documents True
	Common Attributes ('id',)
	Attributes Summary
	Attribute Data type #Unique values Has empty value
	──────────────────────────────────────────────────────────
	id ('str',) 10 False
	Storage Summary
	Backend SQLite (https://www.sqlite.org)
	Connection my_connection
	Table Name my_table_name
	Serialization Protocol
	Class DocumentArraySqlite
	```
	The API is **almost the same** as the deprecated `DocumentArrayMemmap` and is consistent across storage backends and
	in-memory storage. Furthermore, some Document Stores offer fast Nearest Neighbor algorithms and are more convenient in
	production.
	````{admonition} See Also
	:class: seealso
	Read more about [Document Stores](https://docarray.jina.ai/advanced/document-store/) in DocArray
	````
	**New storage options**:
	Jina 2 used to offer persistence of DocumentArray through `DocumentArrayMemmap`. In Jina 3, this data structure is
	deprecated and we introduce different [Document Stores](https://docarray.jina.ai/advanced/document-store/) within the
	`DocumentArray` API. Thus, you can enjoy a consistent `DocumentArray` API across different storage backends and leverage
	modern databases, such as [SQLite backend](https://docarray.jina.ai/advanced/document-store/sqlite/), while using an API that is **almost the same** as the deprecated `DocumentArrayMemmap`.
	For example, you can use [SQLite backend](https://docarray.jina.ai/advanced/document-store/sqlite/) as a replacement
	for `DocumentArrayMemmap`, which lets you persist Documents to disk and load them in another session:
	````{tab} Storing to disk
	```python
	from docarray import Document, DocumentArray
	docs = DocumentArray(storage='sqlite', config={'connection': 'my_connection', 'table_name': 'my_table_name'})
	docs.extend([Document() for _ in range(10)])

````{tab} Loading from disk
```python
from docarray import DocumentArray
docs = DocumentArray(storage='sqlite', config={'connection': 'my_connection', 'table_name': 'my_table_name'})
```

I removed the info box at the bottom because it just links to storage backends, but those are already linked at the top. I tried to cut as much as possible while still keeping the key information in place.

[JohannesMessner]

Ok so the code suggestion is messed (the box with the second tab should be inside of it) up but yeah

[github-actions]

📝 Docs are deployed on https://docs-sqlite-migration--jina-docs.netlify.app 🎉

[JohannesMessner]

concise enough for me now ;)