What databases are used with javascript?
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CategoriesDiscussions List hand-picked by Openbase ExpertsLearn MoremongooseMongoDB object modeling designed to work in an asynchronous environment.MIT TypeScript Definitions: Built-In GitHub Stars 24.8K Weekly Downloads 2M Last Commit 7mos ago User Rating 4.7/ 5 316 Top Feedback 72Great Documentation 67Easy to Use 60Performant redisA high-performance Node.js Redis client.MIT TypeScript Definitions: Built-In GitHub Stars 15.5K Weekly Downloads 3M Last Commit 6mos ago User Rating 4.8/ 5 115 Top Feedback 20Performant 18Great Documentation 18Easy to Use mongodbThe Official MongoDB Node.js DriverApache-2.0 TypeScript Definitions: Built-In GitHub Stars 9.5K Weekly Downloads 3.9M Last Commit 5mos ago User Rating 4.7/ 5 73 Top Feedback 35Great Documentation 33Easy to Use 26Performant What do you use when you only need to store small amounts of dataWe’re used to thinking about databases as huge storage platforms where we can throw all the data we need, and then retrieve it by some form of a query language. Scaling these databases, keeping the information consistent and fault-tolerant is a challenge on its own. However, what happens when our data needs are very small? What happens when RedShift, BigQuery, and even MySQL are too big of a solution to our tiny-bitty data requirements? Well, as it turns out, there is an app for that. In fact, there are plenty of options, so here I’m going to be covering the top 5 embedded databases for your tiny data needs. What is an embedded database though?When we read the word “embedded” 90% of us jumps to the conclusion that I’m talking about IoT or mobile devices. But this is not the case. Not the only case anyway. Granted, those systems have very limited resources which makes most traditional database systems hard to configure and install there. But there are other use cases for small databases and that is embedding them as part of a software product. For example, imagine a search done on a big code repository through your IDE. The IDE could have embedded a reverse-index database that would allow you to search for keywords and get a quick reference to the relevant files. Or maybe when performing a search on your favorite email desktop client, that one most likely has an embedded database as well. All emails are stored and indexed there so you can access that information quickly and easily. Another big benefit from embedded databases that you might’ve picked up on by now, is that they don’t require network calls to interact with. That is a huge performance boost compared to the standard database variety. Essentially while on a normal development you’d want to have your database on its own server (or cluster of servers) so its resource consumption won´t affect the rest of the components of your architecture, for embedded databases you want them as close to the client code as possible. This reduces the latency between them and avoids the dependency on the communication channel (i.e the network). Now this idea can take many shapes, from a quick in-memory database using a JSON file as main storage, to a highly efficient tiny relational database that can be queried using a SQL-like language. Let’s take a look at 5 alternatives. LowDBLet’s start simple, LowDB is a tiny in-memory database. It’s a very basic solution but that solves a very simple use case: needing to store and access JSON-like structures (i.e documents) from JavaScript-based projects. One of the main benefits of LowDB is that it’s meant to be used from JavaScript, which translates to: it can be used for back-end, desktop, and browser code alike. On the back-end you can use it with Node.js, for desktop development it can be integrated into an Electron project, and finally, it can also be run directly on the browser through its integrated JS runtime. The API provided by this database is also quite simplistic and minimal, it doesn’t provide any search functionality out-of-the-box. It’s limiting itself to loading the data of a JSON file into an array variable and letting you (the user) find what you’re looking for however you see fit. For instance, take a look at the following code: As you can see, the interesting part here is not the default behavior but the fact that I’m using an adapter called
It’s highly extensible and compatible with TypeScript, which provides a schema-like behavior for the data storage (i.e you’re not allowed to add data that doesn’t follow a pre-set schema). If you mix those two options, LowDB starts showing some promise as an interesting option to handle local JSON-like data. LevelDBLevelDB is an open-source key-value database built by Google. It is meant to be a super-fast yet very limited key-value storage where data is stored sorted by key out-of-the-box. It only has three basic operations: Put, Get and Delete, nothing else — kind of like LowDB if you think about it. And much like LowDB it does not have a client-server wrapper, which means there is no way to communicate with it from any language, if you want to use it, you’ll have to use the C/C++ libraries and if you want a server-like behavior, you’ll have to wrap it yourself. Much like in most of the cases we’ll cover here, the functionality is very basic since they cover a very simple yet needed use case: storing data close to the code and accessing it fast. The database’s storage architecture is around a Log-structured Merge Tree (LSM) which means it is optimized for large sequential write operations instead of small random ones. One major limitation from LevelDB is that it acquires a system-level lock on the storage once opened which means only one process can interact with the database at the time. Of course, you can use multiple threads to parallelize some operations from within that process. But that is the extent of it. Interestingly enough, this database is used as the backend DB for Chrome’s IndexedDB and apparently Minecraft Bedrock edition uses it for some chunk and entity data storage (although by the looks of it, they use a slightly modified version of Google’s implementation). Raima Database ManagerI mentioned IoT before didn’t I? Well Raima is one of the fastest database managers especially optimized to run in resource-restricted IoT devices. What do I mean by resource-constrained environments? Raima only requires 350kb of RAM to operate. That’s what I can minimalistic resource utilization. One of the main characteristics of this solution which hasn’t appear on any of the previous ones, is that it fully supports SQL. It provides a relational data model and allows you to query using the SQL language. It also, unlike LevelDB, allows for multi-process access to the database through a client-server architecture (i.e this one allows you to move away from the source code a bit further than others). And if you decide to go for a close-to-source embedded application, you can also use multithreading to support concurrent access to multiple databases. The flexibility of Raima allows you to go from a traditional client-server approach to the most efficient (and of course limited) use case of a single in-memory database consumed by a single client. But hey, this is a very valid use case for embedded databases. This flexibility makes it a very versatile solution. Of course, each deployment mode will have its own benefits and limitations, but it’ll also be optimized for very specific use cases. So make sure you pick the right one for you and get the most out of this database. Apache DerbyIf you’re looking for another very small, SQL-like database, Apache Derby might very well be what you were looking for. Derby is completely written in JAVA which also loses a bit of credit when it claims to only have a 3.5Mb footprint. After all, you can’t run it or use it in any way without also having installed the JVM on the host system. That being said, if your use case allows for the JVM, then fantastic, you can keep considering Derby, otherwise you might want to go for a more native solution like LevelDb or Raima. But as I said, if you’re working on a JAVA project already and have the need to integrate a small, reliable, SQL-based database then Derby is definitely a potential candidate. It comes with an integrated JDBC driver, so there is no need for extra dependencies. It can work both, on an embedded mode inside your JAVA application or as a standalone server, allowing for multiple applications to interact with it concurrently (similar to how Raima does, but without the many variants). The biggest downside to this project to be honest, is its documentation. It might be a standard for the JAVA community but it’s not user-friendly and most of the official links sent readers to a private confluence page. Many other solutions here provide a smoother experience when it comes to documentation which also helps with the adoption of their products. solidDBLast but certainly not least solidDB covers a very interesting case by providing an in-memory relational database that can also boost a persistent model at the same time. Claiming it can keep both data storage options synchronized in real-time. That’s no small claim. Essentially just like other solutions listed here, solidDB can be accessed either through ODBC or JDBC, which allows for JAVA and C applications to interact with it, through SQL. Also like some of the solutions listed here, it can be deployed in several modes:
Multiple big names, such as Cisco, Alcatel, Nokia, and Siemens claim to be using this database for their mission-critical operations due to the lightning-fast speed at which data is accessed. Given all its deployment modes, its extensive documentation, and list of high-demand customers I can see how this is one of the most reliable, stable, and fast embedded databases on this list. Embedded databases are meant to handle a very specific use case either by providing fast and reliable data storage with minimum latency or by allowing fast and secure access to data. The solutions listed here achieve those goals by different means, it’s up to you and your particular context to decide which one is the right fit for you. Have you tried any of these solutions in the past? Have you had the need for an embedded database on one of your projects? What did you decide to go with? Build applications differentlyOSS Tools like Bit offer a new paradigm for building modern apps. Instead of developing monolithic projects, you first build independent components. Then, you compose your components together to build as many applications as you like. This isn’t just a faster way to build, it’s also much more scalable and helps to standardize development. It’s fun, give it a try →  Learn MoreWhat is a JavaScript database?sql. js is a javascript SQL database. It allows you to create a relational database and query it entirely in the browser. You can try it in this online demo. It uses a virtual database file stored in memory, and thus doesn't persist the changes made to the database.
Is SQL compatible with JavaScript?Yes, it's true. You can build Node. js applications with SQL Server! In this tutorial, you will learn the basics of creating a Node.
Does JavaScript work with database?If you want to connect to a MySQL database using JavaScript, you can use Node. js and a library called mysql. You can create queries, and get results as an array of registers. If you want to try it, you can use my project generator to create a backend and choose MySQL as the database to connect.
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