As you get more complex, you're actually creating a database. Whatever you want to call it, a database is just a set of records stored to disk. What you're missing is the complex functionality that has been built into the database systems to make them easier to use.
The main thing that springs to mind is indexing. OK, so you can store 10 or 20 or even or records in a serialised array, or a JSON string and pull it out of your file and iterate it relatively quickly.
Now, imagine you have 10,, ,, or even 1,, records. When someone tries to log in you're going to have to open a file which is now several hundred megabytes large, load it into memory in your program, pull out a similarly sized array of information and then iterate s of thousands of records just to find the one record you want to access. A proper database will allow you to set up indexes on certain fields in records allowing you to query the database and receive a response very quickly, even with huge data sets.
Another thing loosely related to indexing is transfer of information. As I said above, when you've got files of hundreds or thousands of megabytes you're having to load all of that information into memory, iterate it manually probably on the same thread and then manipulate your data. With a database system it will run on its own thread s , or even on its own server. All that is transmitted between your program and the database server is an SQL query and all that is transmitted back is the data you want to access.
You're not loading the whole dataset into memory - all you're sending and receiving is a tiny fraction of your total data set. It sounds like you made an essentially valid, short term data-store technical decision for your application - you chose to write a custom data store management tool. There are specific, very common, predictable, performance problems you will be forced to deal with, and you're better off using existing tools instead of rolling your own.
It sounds like you've written a small custom-purpose database, built into and directly used by your application. I assume you're relying on an OS and file system to manage the actual disk writing and reading, and treating the combination as a data-store.
You're sitting at a sweet-spot for data storage. An OS and file system data store is incredibly convenient, accessible, and cross-platform portable. The combination has been around for so long, that you're certain to be supported, and have your application run, on almost any standard deployment configuration. It's also an easy combination to write code for - the API is fairly straight-forward and basic, and it takes relatively few lines of code to get it working.
You're on a continuum of options, and there are two 'directions' you can go from here, what I think of as 'down' and 'up':.
You can, if you want, go down , that is, bypass the OS and filesystem altogether and really write and read directly from disk.
There are several sub-categories here - these aren't exactly exclusive, though. Some tools span both, providing some functionality in each, some can completely switch from working in one mode to working in the other, and some can be layered on top of each other, providing different functionality to different parts of your application.
You may find yourself needing to store higher and higher volumes of data, while still relying on your own application for managing the data manipulation complexity. A whole range of key-value stores are available to you, with varying extents of support for related functions. NoSQL tools fall into this category, as well as others. There is some wiggle room here - you can force better read consistency, for slower reads. Various tools and options provide data manipulation apis, indexing and other options, which may be more or less suited for easily writing your specific application.
So if the above points almost completely describe your application, you might be "close enough" to work with a more powerful data store solution.
The "SQL" family of data storage application, as well as a range of others, are better described as data manipulation tools, than pure storage engines. They provide a wide range of additional functionality, beyond storage of data, and often beyond what's available in the key-value store side of things. You'll want to take this path when:. This is the more "traditional" way of thinking of a database or data store, and has been around for much longer - so there is a lot that's available here, and there's often a lot of complexity to deal with.
There are several, modern, third-party tools and libraries, which interpose themselves between your data storage tools and your application, to help you manage the complexity. They attempt to initially take away most or all of the work that goes into managing and manipulating data stores, and, ideally, allow you to make a smooth transition into complexity only when and if it is required. This is an active area of entrepreneurship and research, with a few recent results that are immediately accessible and useable.
It is hard to be fair here as there are literally dozens of tools and libraries which act as wrappers around the APIs of various data stores. PS: if you prefer videos to text, you might want to watch some of Rich Hickey's database related videos; he does a good job of elucidating most of the thinking that goes into choosing, designing and using a data store. When you have simple data, like a list of things as you describe in the comments of your question, then an SQL database won't give you much.
A lot of people still use them, because they know their data can get more complicated over time, and there are a lot of libraries that make working with database trivial. But even with a simple list that you load, hold in memory, then write when needed, can suffer from a number of problems:. Abnormal program termination can lose data, or while writing data to disk something goes wrong, and you can end up killing the whole file.
You can roll your own mechanisms to handle this, but databases handle this for you using battle-proven techniques. If your data starts growing too big and updating too often, serializing all your data and saving is going to be a big resource hog and slow everything down.
You'd have to start working out how to partition things, so it won't be so expensive. Databases are optimized to save just the things that change to disk in a fault tolerant way. Also they are designed, so you can quickly just load the little bits of data you need at any given time.
Also, you don't have to use SQL databases. But it is done in a fault-tolerant way, and in a way where the data can intelligent split up, queried, and intelligently split across multiple computers. Also, some people mix things up. Then use relational databases to store more complex data where they need to do more interesting queries.
A file system fits the description of a NoSQL database, so I'd say you should definitely consider using that when deciding on how to store your data and not just dismiss it off hand in favor of RDBMS, like some answers seems to suggest here. One issue with file systems and NoSQL in general is handling relationships between data.
Also remember the positive sides of using a file system as storage:. I see a lot of answers focus on the problem of concurrency and reliability. Databases provide other benefits beside concurrency, reliability and performance.
They allow to not to bother how bytes and chars are represented in the memory. In other words, databases allow programmer to focus himself on "what" rather than "how". One of the answers mentions queries. As code evolves during the development simple queries such as "fetch all" can easily expand to "fetch all where property1 equals this value and then sort by property2" without making it programmer's concern to optimize data structure for such query.
Performance of most queries can be speed up by making index for a certain property. Other benefit are relations. With queries it's cleaner to cross-reference data from different data sets then having nested loops. For example searching for all forum posts from users that have less then 3 posts in a system where users and posts are different data sets or DB tables or JSON objects can be done with a single query without sacrificing readability.
All in all, SQL databases are better then plain arrays if data volume can be big let's say more than objects , data access in non-trivial and different parts of code access to different subset of data.
File systems are a type of database. You're provide keys file name to look-up data file contents , which has abstracted storage and an API by which your program communicates. So, you are using a Database. The other posts can argue about the virtues of different types of database Then the database serves to prevent them from overwriting each others changes. You also need a database when your data is larger than memory.
Nowadays with the memory we have available, this does indeed makes the use of databases in many applications obsolete. Your approach is definitely better than the nonsense of "in-memory databases".
Which are essentially your approach, but with a lot of overhead added. Too many applications are built with a design process that automatically assumes all the required tools and frameworks at the beginning.
Relational databases are so common and many developers have worked on similar applications as before, that they're automatically included before the project starts. Many projects can get away with this, so don't judge too harshly. You started your project without one, and it works. It was easier for you to get this up and running without waiting until you SQL. There is nothing wrong with that.
As this project expands and the requirements become more complicated, some things are going to become difficult to build. Until you research and test alternate methods, how do you know which is better? You can ask on Programmers and weed through the flames and 'it depends' to answer this question. Once you learn it, you can consider how many lines of code you're willing to write in your language to handle some of the benefits of a database.
At some point, you're reinventing the wheel. Easy is often relative. There are some frameworks that can build a web page and connect a form to a database table without requiring the user to write any code. I guess if you struggle with the mouse, this could be a problem. Everyone knows, this isn't scalable or flexible because god forbid you've tightly coupled everything to the GUI. It's easy to do. That's why someone created them in the first place.
It doesn't seem like such a huge investment in order to make an informed decision. You could probably do a performance test as well. Saving the data to disk IS writing it to a database, especially if you put each object in its own file with the name of the file being the key to the record. And to minimize lookup times for reading the file, create subdirectories based on the first few characters of the key.
Choose your naming scheme based on the distribution of your keys. That is a database and if it does all that you need, then do it that way. A database is typically designed so that it is easy to store and access information. A good database is crucial to any company or organisation.
This is because the database stores all the pertinent details about the company such as employee records, transactional records, salary details etc. A database stores and manages a large amount of data on a daily basis.
This would not be possible using any other tool such as a spreadsheet as they would simply not work. A database is pretty accurate as it has all sorts of build in constraints, checks etc. In this lesson, we will discuss what a database does and how to decide whether you need a database to manage your information.
A database allows you to store information related to a specific topic in an organized way. In addition to storing data, you can sort , extract , and summarize information related to the data. One of the software programs that allows you to do this is Microsoft Office Access , which is a database creation and management program.
Access Example. There are many types of data you may need to store and manage —text and numbers, for example. Depending on what you want your data to do for you, you may or may not need to use a database. You might be able to use a spreadsheet program like Microsoft Excel. How do you know which data can be adequately managed with Excel and which data requires Access to manage it more efficiently? It depends on how much data you have to manage and what you want your data to do for you.
Let's try to answer this by looking at a bookstore scenario. If you work for a bookstore business, you might have to keep track of your customers and their orders. You could use Microsoft Excel to store and manage this type of data; however, Excel is a spreadsheet software program that is traditionally used to manage numerical information , like totaling up all purchases by one customer.
While it can do an adequate job of storing some types of text-based data —like a customer's name and contact information —it's not really what Excel was designed to do. The examples on the following pages will show you why an Access database may be a better choice for the bookstore business.
In Excel, you can store your data in a worksheet so you can mail promotional information to an entire list or sort to find specific customers to target mail. You can even filter customer information to display all of the customers who live in a particular state, like in the following image.
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