I have a large PHP application and a MySQL Database for my company. All communications such as emails, quotes which are HTML based, are surrently stored in "text" columns in MySql tables. These tables have grown to be quite large now, 15-16GB in size, and are slow to restore, move to other servers etc.
Is there a more modern approach to storing information of this nature, perhaps a different kind of database altogether which is perfect for storing documents. Obviously this data would need to be retrievable from the core application etc.
I've heard of things such as MongoDB but don't know if these are designed to cater for this kind of storage.
Does anyone have any suggestions on how to move away from "Text" columns? I'm sure this must be an old fashioned technique by now.
Regards
James
It would appear that your question is "What options exist for storing data because I think TEXT columns in relational databases are old-fashioned?".
Regarding the question...there's lots of different tools and substrates for storing data - apart from processing, that's what computers do. As to which is the most appropriate, well that depends on how you want to access the data, update it and dispose of it: how robust these mechanisms need to be : how fast they need to operate.
don't know if these are designed to cater for this kind of storage.
But the only thing you've told us about the storage is that there is a lot of it. You should certainly acquaint yourself with the CAP theorem. It looks deceptively simple. But you're going to get into a lot of problems mixing different databases in the same application if you don't know exactly what you're doing.
and are slow to restore, move to other servers etc.
I don't know what you mean by "etc". But if your problem is the size of the data, then the solution is to simply partition the dataset - and its probably more practical to do this in tables with a unified view than to use MySQL's table partitioning.
Depending on the size of the data, you might also consider compressing the HTML data before inserting it - after all, you can't index it.
Yes, you could rewrite your application to run on a NoSQL database - if you exclusively use trivial ORM that should be straightforward. But it doesn't reduce the volume of data.
Related
I am working on my masters thesis. For my implementation I have some MySQL tables.
With every iteration my table structure will differ (adding, removing columns etc). I was wondering what the best way is to handle the ever changing structure, without changing old code too much.
I read that Facebook has a version control system where the can specify exactly what kind of code/feature is available and for what user. As far as I know that must mean that they manage many different database structures at once. How does their old code work along side their new code with respect to their database? Do they do a lot of testing? Did they abandon MySQL all together?
Personally I like FriendFeeds Solution a lot. However I am wondering if it is too much for me.
Why anyone would try to use a relational database for non-relational data.
Forget about FriendFied and take a look at NoSQL solutions. They are schemaless, they support horizontal scalability much better than any RDBS and most of them are free/open source.
I can recommend MongoDB. It's very fast, written in C++, but no ACID complaint.
Also you could try RavenDB. It's not as fast as MongoDB and inserts are very slow compared to Mongo, but it's ACID complaint. Written in .NET.
So I have a website that could eventually get some pretty high traffic. My DB implementation is in SQL Server 2008 at the moment. I really only have 2 tables and a few stored procs. Most of the DB could be re-designed to work without joining (although it wouldn't make sense when I can join so easily within SQL Server).
I heard that sites like Digg and Facebook use NoSQL databases for a lot of their basic data access. Is this something worth looking into, or will SQL Server not really slow me down that bad?
I use paging on my site (although this might change in the future), and I also use AJAX'd data access for most of the "live" stuff, so it doesn't really seem to be a performance hindrance at the moment, but I'm afraid it will be as the data starts expanding exponentially.
Am I going to gain a lot of performance my moving to NoSQL? Honestly, right now I don't even completely understand NoSQL, so any tips on how this will help me improve the better.
Thanks guys.
Actually Facebook use a relational database at its core, see SOCC Keynote Address: Building Facebook: Performance at Massive Scale. And so do many other web-scale sites, see Why does Quora use MySQL as the data store instead of NoSQLs such as Cassandra, MongoDB, CouchDB etc?. There is also a discussion of how to scale SQL Server to web-scale size, see How do large-scale sites and applications remain SQL-based? which is based on MySpace's architecture (more details at Scale out SQL Server by using Reliable Messaging). I'm not saying that NoSQL doesn't have its use cases, I just want to point out that there are many shades of gray between white and black.
If you're afraid that your current solution will not scale then perhaps you should look at what are the factors that prevent scalability with your current solution. Test data is cheap to produce, load the 'exponentially increased' data volume and run your test harness, see where it cracks. None of the NoSQL solutions will bring magic off-the-shelf scalability, they all require you to understand how to use them effectively and deploy them correctly. And they also require you to test with large volumes if you want to ensure success at scale. Same for traditional relational solutions.
Sql Server scales pretty well. For example, Stack Overflow used it to serve you this very page. Facebook and Google might use a form of nosql, but even if you make it really big you're unlikely to rise to that level.
With a simple table structure and data that fits on one server, it doesn't matter much what platform you use. There are a several possible reasons to need to move to NoSQL:
Data scaling - SQL works best when all the data fits on one server (up to a few TB). The reason a lot of NoSQL stores don't have join is that they were designed not to require all the objects to be on one server.
Performance scaling - NoSQL stores do tend to be faster at handling high traffic, but not necessarily by enough to matter. You can improve SQL performance quite a lot with replication and caching as long as you aren't running into data size issues. Writes generally do have to run on the one server, but in most cases you will need to improve read performance long before write performance becomes an issue.
Complex data access - some types of queries simply don't fit well into a relational model. Graph and set stores work quite differently from relational databases so are a better fit for some applications.
Easier development - If you don't already have a SQL database and all the code to support it, using a schemaless datastore can save quite a bit of development time.
I don't think so you have to move your database from SQL to NoSQL unless and untill you are serving thousands of TB data. If you properly normalize your tables and serve the data and also need to set proper archive mechanism it should work.
If you still have question what to choose and how, than check this. Let's assume that you have decided to move on to NoSQL database than there are lot of market player. Just have a look at the list which is again depending upon your need and type of data you have.
Am I going to gain a lot of performance my moving to NoSQL?
It depends.
Check out this article for 7 reasons when you DON'T want to use NoSQL. If none is your case, then read further.
The main advantage of Document-based NoSQL for the traditional enterprise needs is cheaper hosting at high scale due to lower CPU usage on querying denormalised data (the most often request). Key points:
The CPU is going nuts on JOINs and GROUP BYs in the SQL queries, when a denormilised data structure implies no/less JOINs, hence less stress on CPU.
CPU is the most expensive resource in the cloud, then storage is the cheapest. And denormalised data trades higher storage for lower CPU.
How to get there?
Master the DDD (Domain-Driven Design).
Gain good understanding of CQRS (Command Query Responsibility Segregation) and Eventual consistency.
Understand your domain and business processes.
Design model, which is tuned to the access patterns.
Review.
Repeat steps 3 - 5.
i am writing code for friend list and messaging system for my college website.I need to store interconnected data.. need to search them ...It has about 3500 records..So which way I proceed MYSQL or XML ..which is fastest..which is best ?why?
I'm going to use one of my professor's favorite answers here: "it depends."
XML and MySQL have very different applications. If you need to be doing lots of simultaneous queries for all sorts of sophisticated things, MySQL is your clear winner. Sometimes MySQL can be hard to use in some applications because you must first create a database schema in which to fit your data. It sounds like though, that you have many records with the same structure, and it would be easy enough to throw them into a database. With a SQL based database engine like MySQL, you can also construct queries using the standard SQL language. Database optimizations can also help to increase the performance of these types of queries, for example, you can used indexes and keys. If your data needs to be updated regularly, than MySQL will likely provide better performance as it will not have to rewrite the XML file. If you need your application to scale to many simultaneous connections of sophisticated queries, you are definitely going to want to go with some sort of SQL solution.
Depending upon your application though, sometimes there are other ways to store and access your data. I for one once needed to create a persistent data structure on the disk which could be accessed very quickly, but never updated. For that, I used cdb. There are also other database systems out there like the Berkeley database, and some No-SQL solutions such as couchdb and mongodb. I posed a somewhat interesting question here on stackoverflow on the use of No-SQL solutions a little while back which you may find interesting as well.
This is really just a sampling of different considerations you may want to make when you are choosing how you want to store your data. Think about questions like: How frequently will things be queried? or updated? What will your queries look like? What kinds of applications do you need to access your information from? etc.
Right now I'm developing the prototype of a web application that aggregates large number of text entries from a large number of users. This data must be frequently displayed back and often updated. At the moment I store the content inside a MySQL database and use NHibernate ORM layer to interact with the DB. I've got a table defined for users, roles, submissions, tags, notifications and etc. I like this solution because it works well and my code looks nice and sane, but I'm also worried about how MySQL will perform once the size of our database reaches a significant number. I feel that it may struggle performing join operations fast enough.
This has made me think about non-relational database system such as MongoDB, CouchDB, Cassandra or Hadoop. Unfortunately I have no experience with either. I've read some good reviews on MongoDB and it looks interesting. I'm happy to spend the time and learn if one turns out to be the way to go. I'd much appreciate any one offering points or issues to consider when going with none relational dbms?
The other answers here have focused mainly on the technical aspects, but I think there are important points to be made that focus on the startup company aspect of things:
Availabililty of talent. MySQL is very common and you will probably find it easier (and more importantly, cheaper) to find developers for it, compared to the more rarified database systems. This larger developer base will also mean more tutorials, a more active support community, etc.
Ease of development. Again, because MySQL is so common, you will find it is the db of choice for a great many systems / services. This common ground may make any external integration a little easier.
You are preparing for a situation that may never exist, and is manageable if it does. Very few businesses (nevermind startups) come close to MySQL's limits, and with all due respect (and I am just guessing here); the likelihood that your startup will ever hit the sort of data throughput to cripple a properly structured, well resourced MySQL db is almost zero.
Basically, don't spend your time ( == money) worrying about which db to use, as MySQL can handle a lot of data, is well proven and well supported.
Going back to the technical side of things... Something that will have a far greater impact on the speed of your app than choice of db, is how efficiently data can be cached. An effective cache can have dramatic effects on reducing db load and speeding up the general responsivness of an app. I would spend your time investigating caching solutions and making sure you are developing your app in such a way that it can make the best use of those solutions.
FYI, my caching solution of choice is memcached.
So far no one has mentioned PostgreSQL as alternative to MySQL on the relational side. Be aware that MySQL libs are pure GPL, not LGPL. That might force you to release your code if you link to them, although maybe someone with more legal experience could tell you better the implications. On the other side, linking to a MySQL library is not the same that just connecting to the server and issue commands, you can do that with closed source.
PostreSQL is usually the best free replacement of Oracle and the BSD license should be more business friendly.
Since you prefer a non relational database, consider that the transition will be more dramatic. If you ever need to customize your database, you should also consider the license type factor.
There are three things that really have a deep impact on which one is your best database choice and you do not mention:
The size of your data or if you need to store files within your database.
A huge number of reads and very few (even restricted) writes. In that case more than a database you need a directory such as LDAP
The importance of of data distribution and/or replication. Most relational databases can be more or less well replicated, but because of their concept/design do not handle data distribution as well... but will you handle as much data that does not fit into one server or have access rights that needs special separate/extra servers?
However most people will go for a non relational database just because they do not like learning SQL
What do you think is a significant amount of data? MySQL, and basically most relational database engines, can handle rather large amount of data, with proper indexes and sane database schema.
Why don't you try how MySQL behaves with bigger data amount in your setup? Make some scripts that generate realistic data to MySQL test database and and generate some load on the system and see if it is fast enough.
Only when it is not fast enough, first start considering optimizing the database and changing to different database engine.
Be careful with NHibernate, it is easy to make a solution that is nice and easy to code with, but has bad performance with large amount of data. For example whether to use lazy or eager fetching with associations should be carefully considered. I don't mean that you shouldn't use NHibernate, but make sure that you understand how NHibernate works, for example what "n + 1 selects" -problem means.
Measure, don't assume.
Relational databases and NoSQL databases can both scale enormously, if the application is written right in each case, and if the system it runs on is properly tuned.
So, if you have a use case for NoSQL, code to it. Or, if you're more comfortable with relational, code to that. Then, measure how well it performs and how it scales, and if it's OK, go with it, if not, analyse why.
Only once you understand your performance problem should you go searching for exotic technology, unless you're comfortable with that technology or want to try it for some other reason.
I'd suggest you try out each db and pick the one that makes it easiest to develop your application. Go to http://try.mongodb.org to try MongoDB with a simple tutorial. Don't worry as much about speed since at the beginning developer time is more valuable than the CPU time.
I know that many MongoDB users have been able to ditch their ORM and their caching layer. Mongo's data model is much closer to the objects you work with than relational tables, so you can usually just directly store your objects as-is, even if they contain lists of nested objects, such as a blog post with comments. Also, because mongo is fast enough for most sites as-is, you can avoid dealing the complexities of caching and generally deliver a more real-time site. For example, Wordnik.com reported 250,000 reads/sec and 100,000 inserts/sec with a 1.2TB / 5 billion object DB.
There are a few ways to connect to MongoDB from .Net, but I don't have enough experience with that platform to know which is best:
Norm: http://wiki.github.com/atheken/NoRM/
MongoDB-CSharp: http://github.com/samus/mongodb-csharp
Simple-MongoDB: http://code.google.com/p/simple-mongodb/
Disclaimer: I work for 10gen on MongoDB so I am a bit biased.
I have huge database (kinda wordnet) and want to know if it's easier to use Cassandra instead of MySQL|PostrgreSQL
All my life I was using MySQL and PostrgreSQL and I could easily think in terms of relational algebra, but several weeks ago I learned about Cassandra and that it's used in Facebook and Twitter.
Is it more convenient?
What DBMS are usually used nowadays to store social net's data, relationships between objects, wordnet?
There is nothing like a Silver bullet solution, everything is built to solve specific problem and has its own pros and cons. It is up to you to decide - what problem statement you have and what is best solution that fits your problem. Whether you use Cassandra (NoSQL) or MySQL(RDBMS), it is all driven from your system's requirements. Below are the inputs that will help you in taking better decision while deciding on database.
Why to Use NoSQL
In the case of RDBMS database, making choice is quite easy because almost all the databases like MySQL, Oracle, MS SQL, PostgreSQL in this category offer almost same kind of solutions oriented to the ACID property. When it comes to NoSQL, decision becomes difficult because every NoSQL database offers different solution and you have to understand which one is best suited for your app/system requirement. For example, MongoDB fits for use cases where your system demands schema-less document store. HBase might fit for Search engines, analysing log data, any place where scanning huge, two-dimensional join-less tables is a requirement. Redis is built to provide In-Memory search for varieties of data structures like tree, queue, link list etc and can be good fit for making real time leader board, pub-sub kind of system. Similarly there are other database in this category (including Cassandra) which fits for different problems. Now lets move to original question, and answer them one by one.
When to use Cassandra
Being a part of NoSQL family, Cassandra offers solution for problem where your requirement is to have very heavy write system and you want to have quite responsive reporting system on top of that stored data. Consider use case of Web analytics where log data is stored for each request and you want to built analytical platform around it to count hits by hour, by browser, by IP, etc in real time manner. You can refer to blog post (http://blogs.shephertz.com/2015/04/22/why-cassandra-excellent-choice-for-realtime-analytics-workload/) to understand more about the use cases where Cassandra fits in.
When to Use a RDMS instead of Cassandra/NoSQL
Cassandra is based on NoSQL database and does not provide ACID and relational data property. If you have strong requirement of ACID property (for example Financial data), Cassandra would not be a fit in that case. Obviously, you can make work out of it, however you will end up writing lots of application code to handle ACID property and will loose on time to market badly. Also managing that kind of system with Cassandra would be complex and tedious for you.
There are many different flavours of "NoSQL" databases. If your application is really like Wordnet perhaps you should look at a graph database such as Neo4j.
I would suggest to analyse your request.
If you are going with more clusters, machines take NoSQL
If your data model is complicated - require efficient structures take NoSQL (no limits with type of columns)
If you fit in a few machines without scales, and you don't need super performance for multi request (as for example in social network - where lot of users send http request), and you don't think you involve saleability take RDBMS (Postgres have some good functions and structures which you can use, like array column type).
Cassandra should work better with large scales of data, multi purpose.
neo4j - would be better for special structures, graphs.
Cassandra and other NoSQL stores are being used for social based sites because of their need for massive write based operations. Not that MySQL and Postgres can't achieve this but NoSQL requires far less time and money, generally speaking.
Sounds like you may want to look at Neo4J though, just in terms of your object model needs.
All different products and they all have their pro's and conn's. What kind of problem do you have to solve?
Huge, as in TB's?