I'm creating a project, with web-mail functionality among others. We have MongoDB as main DBMS, but on huge amounts of emails, it becomes overloaded with message bodies.
We've tried to store message bodies on server HD and on S3 node, but it's not very efficient.
Is there any good solution for key-value storing of huge number of files (possibly cloud storage, or some NoSQL DBMS or anything else)?
You may be over-thinking/over-designing the DBMS component. You may want to consider Berkeley DB as your data store. It supports several APIs, including a Key/Value API (NoSQL). It's highly scalable, reliable and very fast. Berkeley DB is used heavily in commercial and open source email projects, including OpenWave, Critical Path, Postfix, SendMail and others. Because of it's embedded nature, small foorprint, developer-friendly key/value pair API and totally configurable from within the embedding application, it's a frequent choice for email data management.
Disclaimer: I'm the Product Manager for Berkeley DB, so I'm a little biased. That said, Berkeley DB is used by those products and many more more email data management.
Related
I keep a content revision history for a certain content type. It's stored in MongoDB. But since the data is not frequently accessed I don't really need it there, taking up memory. I'd put it in a slower hard disk database.
Which database should I put it in? I'm looking for something that's really cheap and with cloud hosting available. And I don't need speed. I'm looking at SimpleDB, but it doesn't seem very popular. rdbms doesn't seem easy enough to handle since my data is structured into documents. What are my options?
Thanks
Depends on how often you want to look at this old data:
Why don't you mongodump it to your local disk and mongorestore when you want it back.
Documentation here
OR
Setup a local mongo instance and clone the database using the information here
Based on your questions and comments, you might not find the perfect solution. You want free or dirt cheap storage, and you want to have your data available online.
There is only one solution I can see feasible:
Stick with MongoDB. SimpleDB does not allow you to store documents, only key-value pairs.
You could create a separate collection for your history. Use a cloud service that gives you a free tier. For example, http://MongoLab.com gives you 240Mb free tier.
If you exceed the free tier, you can look at discarding the oldest data, moving it to offline storage, or start paying for what you are using.
If you data grows a lot you will have to make the decision whether to pay for it, keep it available online or offline, or discard it.
If you are dealing with a lot of large objects (BLOBS or CLOBS), you can also store the 'non-indexed' data separate from the database. This keeps the database both cheap and fast. The large objects can be retrieved from any cheap storage when needed.
Cloudant.com is pretty cool for hosting your DB in the cloud and it uses Big Couch which is a nosql thing. I'm using it for my social site in the works as Couch DB (Big Couch) similar has an open ended structure and you talk to it via JSON. Its pretty awesome stuff but so weird to move from SQL to using Map-Reduce but once you do its worth it. I did some research because I'm a .NET guy for a long time but moving to Linux and Node.js partly out of bordom and the love of JavaScript. These things just fit together because Node.js is all JavaScript on the backend and talks seemlessly to Couch DB and the whole thing scales like crazy.
I'm making a site to document browser bugs where users can submit a bug and users can submit solutions/workarounds to these bugs. I'll have stuff like:
screenshots of bugs
browser rendering engines
browsers
tags for each bug
bug categories ( css, html, js )
solutions per bug which include code snippets
usual date/time, author, date modified
Since I'm just starting this site, I won't really need to scale off the bat. I'm just wondering if the data is more ideal for something like redis, or should I stick with rdbms ( in my case, Postgres )?
Bug information revolves around products and users, and that data benefits from relational structure. (You can look at a host of existing bug trackers for examples). If you do find you'd need hierarchical data structures (like redis leans toward), there are several different implementations of tree structures in traditional sql, and postgres offers some additional constructs like arrays and ltree structures. Additionally, Postgres has fairly proven methods for storing binary data (like screenshots) and large text data, that depending your nosql engine might not be as stable as you'd hope. I guess there might be some benefit of learning another system (otoh, others woul argue learning your existing tools better is more beneficial), but from a technical standpoint there isn't really an advantage.
MySQL as well Postgress development teams do not recommend storing images and binary data inside the database.
Instead you can store the images in some directory, and filename can be either the ID from the database, or md5(ID + secret) if you worry people may "hack" the system and see images they must not see.
Doing this you will benefit with smaller database also faster access - you can serve the images directly with your webserver.
I am huge Redis fan, but this project looks more like RDBMS for me.
I'm developing a cms for a company that has multiple regional sites (us, uk, china, russia, etc..). Should I use a separate database for each of these sites or use a single database with a 'site' field in each table? My main concern is the table language encoding (ie, can storing strings in different langauges in the same table cause problems, such as sorting issues).
That depends. If you store separate data on the different sites, you should use separate databases. It is much faster and safer, though more expensive. You should also use separate databases if you want to share the same data over the sites, but you expect a heavy load. However, in this case you need a way to synchronise the data between the sites. If you store the same data and your application is not speed critical, then a centralised storage may suffice (but only experience will show if it is fast enough or not).
From what you wrote, I suspect that the first case is true (you store separate data per site), but I can't be sure.
Edit: You may also ask this on Server Fault, there are more experienced administrators there.
The benefits of a non-relational database (such as a key-value pair storage) are evident when used in large scale datasets (google, facebook, linkedin). How do you think small to medium sized applications can benefit from using non-relational databases?
IBM Mainframes have had "non-relational" databases since the 60s (hierarchial databases such as IMS + variants). These databases are still in use because they are extremely fast and handle huge scale well.
The point of relational databases was to provide a regular, relatively abstract method for storing and retrieving data in which the tuning can be done relatively independently of the data model (not true for IMS). They were designed rather in reaction to the inability to reorganize hiearchical databases easily. The upside is nice organization; the downside is medium, not high performance.
Google provides scalable storage and MapReduce to handle scale. It isn't relational.
There was a huge push early in the last decade to store data in XML, in essentially hiearchical form because XML is implicitly hierarchical. That was a huge mistake IMHO, because it repeated the inconvenience of heirarchical databases, but had none of the performance. I'm not very surprised this movement seems to have pretty much died.
Most of the practical push to non-relational seems to me to be towards performance and scale. I don't see how this helps "small" applications much.
People have proposed, but not done a lot of practical data management using knowledge-based schemes. Doug Lenat's CYC comes to mind here. The ability of the database
to help an application draw non-obvious conclusions strikes me a very interesting for "small" applications that are trying be "smart". But there aren't a lot of these yet.
The sweet spot of using a NoSQL database at that scale is when the database model (key-value, document, etc.) is a good match to the application's needs and the advanced relational functionality is not needed.
At the small end of the spectrum, performance is a non issue because just about everything is fast. Storage engines are a non issue, if you don't need a sophisticated query engine, the lack of SQL support is a non issue.
You are left with how well it fits and how easy it is to use. Honestly though, tooling does become an issue. Relational database tooling is mature, NoSQL tooling is less feature rich and less battle hardened. Too often it is roll-your-own tooling. Definitely consider what tools you'd be giving up and how much you need them.
There is an additional slate of advantages for smaller projects when considering a NoSQL service (like Amazon SimpleDB and Microsoft Azure) as compared to a product. If you only have to pay for what you use and you don't use much, it can be cheaper than running a dedicated server, going all the way down to free for something like the SimpleDB free usage tier.
You also avoid some of the server and database maintenance costs. This can be a big win if you don't have a DBA, or when your DBAs are already over worked. Of course you'll still have admin work to do, but it is significantly reduced, and typically simpler.
When it comes to graph databases (like Neo4j - a project I'm involved in) they excel at scaling to complexity. This means, they provide "better substrates for modeling business domains" (see The State of NoSQL, also by Ben Scofield, too). As I see it, this is very important in small to medium sized apps.
This may be better explained through examples, so here's some links to example apps/domain modeling:
Access control lists the graph
database way
Social networks in the database: using a graph database
Domain modeling gallery
The question perhaps requires a bit more context... assuming a Python environment, consider the tutorial at the y_serial project: http://yserial.sourceforge.net/
NoSQL is not merely adopted for reasons of scalability. Serialization (of any arbitrary Python object) and persistence are very convenient at any scale -- so consider the key-value system as one approach.
Well one of the problems with a RDBMS is that you need to spend effort mapping your programming languages domain models to the relational schema of your RDBMS. This effort is usually spent configuring your ORM layer.
With NoSQL databases you are not forced to map your objects to a relational model and in most cases your objects are serialized as-is. Because of the lack of an intermediary schema, data migrations and versioning become easier.
Another benefit is scalability and performance. Since most of the time your data is received by 'keys' effectively everything uses and index. Trivial sharding is possible by doing a % (MOD) on the key against the number of your available NoSQL instances providing natural data partitioning which is crucial for sharding.
If you're interested in seeing how developing with a NoSQL differs from a RDBMS, I have a tutorial where I show how to go about designing a simple blog application using Redis.
If you match up a few common PaaS cloud services like a Key-Value store, a BLOB store, and a Message Queue store you have some handy tools that can free small application developers from the tyranny of the DBA and the infrastructure folks.
Today small developers often resort to Jet MDBs. Why? Easy, shared access is as easy as storing the MDB file on a file share visible to the entire application community. When they can get away with it (i.e. get the necessary support from the gatekeepers) they might use SQL Server Express, MySQL, etc.
Sadly those gatekeepers can be pretty hostile to deal with in a large organization. Mention a "database" and suddenly you face the DBA gang and associated delays, application reviews, prioritization, etc. Mention needing a server and you face that other firing squad.
Using a NoSQL solution and related cloud services can eliminate a ton of this if you don't need an RDBMS.
For one thing, all that's really required is an account with a public cloud provider. This is something that becomes fairly easy once the concept has been approved. And easier for you as a developer once you've been approved and assigned an account, though of course there are the usual bookkeeping issues.
But let's even set that aside. What if your organization implemented a private cloud for such uses? Lots of the issues of outside billing go away, data insecurity worries go away, etc.
Such a thing could be implemented and provisioned in a semi-anonymous fashion, almost as easily as administering file shares. The anonymity comes in because once you've been approved to develop on the in-house cloud nobody needs to nitpick the details of your activities using it any more than they need to examine a request before you can create a file on an existing file share.
Obviously there would be storage and CPU quotas to manage. Nobody can afford to just keep scaling up indefinately. Rogue applications might consume vast quantities of resources. So what you need is some sort of quota system to cap usage. Whether this is monitored by infrastructure folks is an implementation decision, or it might be treated just like file share use: run out and somebody yells at the programmer who in turn looks into it and requests more if appropriate (or fixes his bugs).
But you end up with "utility computing" and by "using no SQL" you don't incur the cost (and issues) of dealing with DBAs. They can still sit quietly surfing the Web in their big offices while you get some work done.
Amazon SimpleDB can be useful for those who need a non-relational database for storage of smaller, non-structural data. Amazon SimpleDB has restricted storage size to 10GB per domain. Amazon SimpleDB offers simplicity and flexibility. SimpleDB automatically indexes all data. Amazon SimpleDB pricing is based on your actual box usage. You can store any UTF-8 string data in Amazon SimpleDB.
I'm deciding between go for a NON-SQL engine or a regular SQL one for a document managment system for small bussines.
I have experience with firebird/sql server and found a good track of reliability (specially with firebird).
This market is full of crappy "servers" (clon-made PC, the mayority), cheap harddisk, rarely use of RAID or anything like that, some are in locations where a power-off is normal, some not have a UPS, etc... (I will include off-site auto-backup to external servers, but that no change the internal setup). (I know about end-user education about such proper setups, but is stupid depend on that, so stick to te point)
From the desing point of view, a schema-less database is the way to go for my system, but, I worry if any of the actual solutions (MongoDb, Tokyo Cabinet, etc) are like firebird and survice crash, malfunctions & abuse so data corruption is very rare.
The plan is store the office documents there & provide a central repository.
Check out Neo4j. It is a graph database (schema-free) that can be used like a document or key/value store.
Neo4j has been in production for many years in environments like you describe. Unlike many other NOSQL databases Neo4j actually flushes data to disk and uses a transaction log to recover from an inconsistent state. It also has real transactions (full ACID) that can span multiple operations and treat them as a single unit (which also seems to be a feature that is frequently left out in many other NOSQL stores).
-Johan
(Disclaimer: I am part of the Neo4j team)
CouchDB has the reliability you need:
The CouchDB file layout and commitment system features all Atomic Consistent Isolated Durable (ACID) properties. On-disk, CouchDB never overwrites committed data or associated structures, ensuring the database file is always in a consistent state.
Look at the ACID Properties section here for more info.
With CouchDB you also get easy backup and replication.
I've no code in production using CouchDB yet, but so far I'm very happy with the tests and the development process with CouchDB.