Database – at what size of data does it become beneficial to move from sql to nosql_ – software engineering stack exchange database etl

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One of the problem with scaling RDBMSes is that by design they are ACID, which means transactions and row level locks (or even table level in some older/simpler RDBMSes). Database interview questions It can be limiting factor if you have lot of queries modifying lot of data running at same time. Database examples NoSQL solutions usually go for eventual consistency model. Database definition How do RDBMS scale on data size?

It’s not entirely true that RDBMS cannot scale on data size, there are two alternatives: vertical partitioning and horizontal partitioning (aka sharding).

Vertical partitioning is basically keeping unrelated tables on separate DB servers, thus keeping size of each one below thresholds mentioned above.


Database architect This makes join these tables using plain SQL less straight forward and less efficient.

Sharding means distributing data from one table among various servers, based on specific key. Database administrator jobs This means that for look ups you know which server to query based on that key. Database architecture However, this complicates queries that are not look ups on the sharding key.

@vartec So you want to drop my 2 years old mail from my mail database as I search through it only once per month whereas my main working set are the last ten mails only?

SQL has problems with some sorts of analysis, but it doesn’t take much data to trigger the problem. Database acid For example, consider a single table with a column that references other rows based on a unique key. Database as a service Typically, this might be used to create a tree structure. Database analyst salary You can write fast SQL statements that reference the related row. Database application Or the related row’s related row. Database architect salary In fact you can make any specific number of jumps. A database is a collection of But if, for each row, you want to select a field on the first related row in the chain that meets some criterion, then it gets complicated.

Consider a table of office locations at nation, province/state, county, town, and village levels, with each office referencing the office it reports to. A database can best be described as There is no guarantee that each office’s reporting office is only one level up. A database is a collection of integrated and related For a selected set of offices, not all on one level, you want to list each one’s associated national office. A database record is an entry that contains This requires loops of SQL statments and will take a long time even today. A database driver is software that lets the (I used to get 30 seconds on a selection of 30 offices, but that was a long time ago–and switching to stored procedures helped a bit.)

So the alternative is to put the whole structure into one big block of data, label it, and store it. Database backup When you want to analyze the data, read all of it into memory at one go, setting up pointers to track the structure, and you can process a couple million offices in the blink of an eye.

None of this has much to do with the amount of data. Database builder The key is the nature of the data’s organization. Database browser If a relational layout helps, then a RDBMS is what you want. Database best practices If not, some kind of bulk storage is going to be anything from slightly to a quadrillion times faster.

Note that if one of these sets of data becomes too big to fit into memory, your non-SQL database doesn’t work any more. Database book Another problem is when you need data from more than one block at a time; you can do this if, and only if, all the blocks fit in memory at once. Database business rules And the user has to wait while you load them up.

If your relational database is going to cause you problems, it will do so before you’ve put much data into it. Database blob The only scaling problem you might have is with your program when the block of data you are assembling for a nosql DB–if you have to use one–becomes too big for it. Database backup and recovery (Do read up on out-of-memory errors. Database building The newer languages sometimes do strange things with memory.)

I think the first reason to go to a NoSQL or Distributed solution isn’t so much the size of all the data, but the size of the tables. Database backend What distributed solutions do well is split up tables to different nodes then when you need to query the tables, each node will process their piece of the table.

RDBMSs can do this, but the new wave of NoSQL databases have been built to do this. Database b tree Oracle, MSSQL, MySQL took their centralized model and tweaked it to make it work in a distributed environment. Yale b database However they still adhere to strict ACID rules while some of the new databases do not adhere to the strict rules such as by using eventual consistency.

There isn’t a set amount of data where you should choose one over the other. Ads b database What needs to be taken into account are the needs of the database and the amount of use it receives. B tree database management system NoSQL databases can process larger data-sets more quickly while relational databases give you the confidence your data is correct with the ACID principles.

It might also be worthwhile in mentioning that your data model has a big influence on things. Database concepts If you find yourself needing to create some form of tree structure (ie you have a self referencing foreign key on a table that contains said foreign key in a compounded primary key) you should probably look at doing that in some form of database that handles those types of data really well (such as mongodb or couchdb).

Like other people have said you should also take into consideration what is happening in your application. Database connection if you really need ACID across multiple tables then you really do need to stick with a RDBMS, but if you have something where you can have some slightly stale data and you need the flexibility of a NoSQL schema (call it schemaless if you like but it still has some form of implicit schema) then you might consider grabbing a NoSQL store ( http://www.10gen.com/customers/craigslist here is an example of why craigslist switched over… Database cardinality but admittedly they are archiving ~10TB of data, which I know doesn’t fit into your small to mid sized database size at all. Database constraints But the use case might be helpful).

Keep in mind that NoSQL systems are not necessarily there to replace RDMS’s but in many instances you can supplement your RDBMS through the idea of Polyglot Persistence and you can store most of your data in an RDBMS but in specific niche instances you can offload some of your data to some form of NoSQL store.

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