nodemailer/wildduck
1
1
Fork 0
mirror of https://github.com/nodemailer/wildduck.git synced 2024-12-31 04:33:09 +08:00
Code Issues Projects Releases Packages Wiki Activity

updated README

Browse source
This commit is contained in:
Andris Reinman 2017-03-09 22:36:50 +02:00
parent 4009a4a8ba
commit 179ba09696
1 changed files with 5 additions and 4 deletions
Show stats Download patch file Download diff file Expand all files Collapse all files

9
README.md
View file

@ -27,7 +27,7 @@ Wild Duck IMAP server supports the following IMAP standards:
### FAQ ### FAQ
**Does it work?** #### Does it work?
Yes, it does. You can run the server and get a working IMAP server for mail store, LMTP and/or SMTP servers for pushing messages to the mail store and HTTP API server to create new users. All handled by Node.js and MongoDB, no additional dependencies needed. Yes, it does. You can run the server and get a working IMAP server for mail store, LMTP and/or SMTP servers for pushing messages to the mail store and HTTP API server to create new users. All handled by Node.js and MongoDB, no additional dependencies needed.
@ -37,16 +37,17 @@ Yes, historically it has been considered a bad practice to store emails in a dat
Notice the word "relational"? In fact documents stores like MongoDB work very well with emails. Document store is great for storing tree-like structures and while GridFS is not as good as "real" object storage, it is good enough for storing the raw parts of the message. Notice the word "relational"? In fact documents stores like MongoDB work very well with emails. Document store is great for storing tree-like structures and while GridFS is not as good as "real" object storage, it is good enough for storing the raw parts of the message.
**Is the server scalable?** #### Is the server scalable?
Not yet. These are some actions that must be done: Not yet. These are some changes that need to be done:
1. Separate attachments from indexed mime tree and store these to GridFS. Currently entire message is loaded whenever a FETCH or SEARCH call is made (unless body needs not to be touched, for example if only FLAGs are checked). This also means that the message size is currently limited. MongoDB database records are capped at 16MB and this should contain also the metadata for the message. 1. Separate attachments from indexed mime tree and store these to GridFS. Currently entire message is loaded whenever a FETCH or SEARCH call is made (unless body needs not to be touched, for example if only FLAGs are checked). This also means that the message size is currently limited. MongoDB database records are capped at 16MB and this should contain also the metadata for the message.
2. Optimize SEARCH queries to use MongoDB queries. Currently only simple stuff (flag, internaldate, not flag, modseq) is included in query and more complex comparisons are handled by the application but this means that too much data must be loaded from database (unless it is a very simple query like "SEARCH UNSEEN" that is already optimized) 2. Optimize SEARCH queries to use MongoDB queries. Currently only simple stuff (flag, internaldate, not flag, modseq) is included in query and more complex comparisons are handled by the application but this means that too much data must be loaded from database (unless it is a very simple query like "SEARCH UNSEEN" that is already optimized)
3. Optimize FETCH queries to load only partial data for BODY subparts 3. Optimize FETCH queries to load only partial data for BODY subparts
4. Parse incoming message into the mime tree as a stream. Currently the entire message is buffered in memory before being parsed. 4. Parse incoming message into the mime tree as a stream. Currently the entire message is buffered in memory before being parsed.
5. Add quota handling. Every time a user gets a new message added to storage, the quota counter should increase. If only a single quota root would be used per account then implementing rfc2087 should be fairly easy. What is not so easy is keeping count on copied and deleted messages.
**What are the killer features?** #### What are the killer features?
1. Start as many instances as you want. You can start multiple Wild Duck instances in different machines and as long as they share the same MongoDB and Redis settings, users can connect to any instances. This is very different from more traditional IMAP servers where a single user always needs to connect (or proxied) to the same IMAP server. Wild Duck keeps all required state information in MongoDB, so it does not matter which IMAP instance you use. 1. Start as many instances as you want. You can start multiple Wild Duck instances in different machines and as long as they share the same MongoDB and Redis settings, users can connect to any instances. This is very different from more traditional IMAP servers where a single user always needs to connect (or proxied) to the same IMAP server. Wild Duck keeps all required state information in MongoDB, so it does not matter which IMAP instance you use.
2. Super easy to tweak. The entire codebase is pure JavaScript, so there's nothing to compile or anything platform specific. If you need to tweak something then change the code, restart the app and you're ready to go. If it works on one machine then most probably it works in every other machine as well. 2. Super easy to tweak. The entire codebase is pure JavaScript, so there's nothing to compile or anything platform specific. If you need to tweak something then change the code, restart the app and you're ready to go. If it works on one machine then most probably it works in every other machine as well.