Need advice about which tool to choose?Ask the StackShare community!

MongoDB

93.6K
80.8K
+ 1
4.1K
SQLite

19.1K
15K
+ 1
535
Add tool

MongoDB vs SQLite: What are the differences?

Introduction

This Markdown code provides a comparison between MongoDB and SQLite, highlighting their key differences.

  1. Storage Structure: MongoDB is a document-oriented database that stores data in a flexible, JSON-like structure called BSON (Binary JSON). It allows for nested data and dynamic schema. On the other hand, SQLite is a relational database that stores data in predefined tables with fixed columns and rows.

  2. Scalability: MongoDB is designed to scale horizontally, allowing for the distribution of data across multiple servers or clusters to handle high volumes of traffic and large datasets. In contrast, SQLite is primarily designed for single-machine use and lacks built-in support for distributed computing.

  3. Query Language: MongoDB uses a powerful and flexible query language known as the MongoDB Query Language (MQL), which supports a wide range of operators and expressions for querying and manipulating data. SQLite, being a relational database, uses SQL (Structured Query Language) for querying and managing data.

  4. Transaction Support: MongoDB provides support for multi-document transactions, allowing operations on multiple documents to be grouped together and either succeed or fail as a single unit. SQLite also supports transactions, but it operates at the level of individual SQL statements rather than documents.

  5. Schema Design: MongoDB's flexible schema design allows for dynamic changes to the schema, making it suitable for evolving data structures and use cases where the schema may change frequently. In contrast, SQLite requires a predefined schema and enforces data integrity through the use of constraints such as primary keys and foreign keys.

  6. Concurrency: MongoDB can handle concurrent read and write operations efficiently, especially when distributed across multiple servers or clusters. SQLite, being a file-based database, has limited concurrency capabilities and is best suited for single-user or low-concurrency scenarios.

In summary, MongoDB and SQLite differ in their storage structure, scalability, query language, transaction support, schema design, and concurrency capabilities.

Advice on MongoDB and SQLite
Emre Emrah
Data Scientist/Back End Developer at Hiddenslate · | 5 upvotes · 47.7K views
Needs advice
on
MongoDBMongoDB
and
MySQLMySQL

Hello everyone. We have a project that it's like a candidate tracking system. It has candidates, projects, assessments, etc. A consultant senior developer started it by using MongoDB. The thing is that he designed the database like it's a relational DB.

Personally, I didn't imagine that it was a good thing to do. Because you won't have the power of SQL functionalities like join, on delete, and more. You have to be very careful, I think things may go unmaintainable very fast. I asked him about this and he said "I don't see a problem doing it like this."

What are your thoughts on this? Did you see examples like this? Should I avoid it or go for it? Any advice is appreciated.

Here is what it looks like in Moon Modeler: https://imgur.com/a/RNwNBNY

See more
Replies (2)
Yoram Kornatzky
Independent Information Technology and Services Professional at DR. YORAM KORNATZKY LTD · | 7 upvotes · 47.3K views
Recommends
on
MySQLMySQL

It happened to me that you actually construct a relational schema with MongoDB. It is not good. You do not use the modeling benefits of MongoDB, and you do not have the benefits of SQL. So I recommend taking it into MySQL. Since you think in a relational way, it is best you move to MySQL

Specifically, do you need non-normalized data? If not, MySQL is best. Otherwise, MongoDB is best. If you think non-relational, you do not need joins, and the problems with cascade disappear.

What is the best way to think? If you work in terms of whole tree of related object, then you think non-relational and non-normalized.

See more
Praveen Pavithran
CTO at Yatis Telematics · | 3 upvotes · 26.6K views
Recommends

It makes no sense if you use MongoDB primarily as a relational database. As you scale MongoDB will be more expensive than SQL and as you said without having the advantages of "join" etc.

We use MongoDB in our company. It is useful for us, as we work with different types of devices and we love the functionality of being able to add fields whenever we have a new device type etc. Mongo also allows enables easy scaling and fault tolerance. However, you will have to learn how to manage it.

If you are already comfortable with SQL and don't need NoSQL, stick to SQL. At scale, it is cheaper than Mongo.

See more
Needs advice
on
FirebaseFirebaseMongoDBMongoDB
and
MySQLMySQL

I have been using Firebase with almost all my web projects as well as SwiftUI projects. I use it for the database as well as the user authentication via Google.

Is it good enough?? I have learned MySQL but I'm not that comfortable…

So for user authentication and database should I keep using firebase or switch to MySQL or MongoDB?? Or any other combination?

See more
Replies (3)
Jesus Flores
New Technologies Developer at Inteliksa · | 4 upvotes · 68.8K views

Hi!

I’m not an expert, but I can tell you some things:

  • Firebase is a great option for a very simple to implement, fast and reliable authentication method. Nonetheless, the free authentications are limited, so if you will potentially have millions of monthly authentications, it’s probably best to take the time to build it into your app directly.
  • MySQL is great for simple tables where the data structures are not too complex, but it lacks some speed when you are trying to retrieve time data series. Also, I believe it’s a bit more difficult to distribute.
  • MongoDB is great when your information is a bit more complex and you need very peculiar data structures, nested data, dynamic structures, etc. For me at least, it’s a bit more complex to master than MySQL, but the freedom it gives you is incredible. It also performs super fast, especially with time data series, and if I’m not wrong, it’s more scalable.

In general, almost all technologies have their good things, it’s just a matter of what you want to do and then choosing the right ones.

See more
Gulshan Prajapati
Project Manager at Touchmeedia Ads · | 4 upvotes · 53.8K views

Look if you are comfortable with firebase you can go with it, after all, It's all about development and running your program bug-free and fast, but firebase is costly fo long run and if you are comfortable with that cost then I suggest you go with it.

See more
Recommends
on
FirebaseFirebase

Doing User authentication (oauth) and session management by ourself is kind a challenging, so if possible use firebase itself since it provides these features out of the box.

See more
Needs advice
on
MongoDBMongoDB
and
MySQLMySQL

I'm starting to work on a Jira-like bug tracker web app. This is a hobby project that is mostly a way for me to learn about different technologies and development processes(CI/CD, etc..) so I could be more ready when I start applying for programming jobs.

I'm debating between MySQL, which I'm less familiar with, and MongoDB which I have used in the past.

My two points of consideration are the following:

1) Which one is more likely to be relevant for web dev jobs? While I want to learn new technologies, I prefer learning ones that will make me more hireable in the future.

2) Which one is more flexible when it comes to changing the shape of the stored data? I expect to need to make some changes as the project goes on.

Thanks, everyone!

See more
Replies (2)
Recommends
on
MySQLMySQL

MySQL is still more popular than MongoDB if you look at Google Trends. I've also added MariaDB, which is pretty much a copy from MySQL and its features, and PostgreSQL, which is also a popular relational database.

This is a very good article for comparing MySQL to MongoDB and which one you should use: MongoDB vs MySQL: A Comparative Study on Databases.

If you just want to learn and you have the time, I would opt for using both MySQL and MongoDB. For example using MySQL for most of the site content and MongoDB for saving log messages. As you get more and more logs you start to see the benefits from MongoDB's faster document fetching.

See more
Andy Gee
Freelance Developer at DGTEpro · | 4 upvotes · 73.6K views
Recommends
on
ClickhouseClickhouseInfluxDBInfluxDB

There's really not an awful lot of difference between the two, they have wildly different storage mechanisms but they each have their fairly similar benefits. If you want to learn something that might be a requisite skill for a job, I would also look at alternatives such as time based and column based systems like InfluxDB and the unbelievably fast and flexible ClickHouse. While they may seem like an unlikely fit for a personal bug tracker app, there's no reason not to use them. Since I got into InfluxDB people have been requesting it a lot and I'll be using ClickHouse for all large databases, probably forever. Expand your horizons beyond your competition's.

See more
Needs advice
on
FaunaFauna
and
MongoDBMongoDB

I’m doing a school project where I have to design a database for a password manager app like 1Password, bitwarden… I’m not sure which database paradigms I should use. Users would have the ability to create vaults and each vault will have many items and can be sorted into favorite, category, tag list… Please help.

See more
Replies (1)
Amr Saber
Backend Engineer at Aster · | 6 upvotes · 30.6K views
Recommends
on
PostgreSQLPostgreSQL

What I have learned through several years of experience, is that by default you should consider SQL database (like PostgreSQL, MySQL, ...) and if does not suit you then you should explore other noSQL options.

SQL is very solid and it can do almost anything and can support almost any kind of systems.

So, for your case I would recommend that you go with SQL. You should start by listing your use cases and infer from them your entities and relations, and work on them in a Top-to-bottom manner, meaning that you should have some entities that are the core dependencies for the other entities. Or, in other words, they can exist without other entities existing, but the opposite is not true, these are your core entities that you should work on first, then gradually build the other entities.

One way to figure out the core entities is to follow how the users will behave in your system, what will the user create first, and what is dependant on other entities.

For example, in your case, on way to do it is to start with the "vault", as everything else cannot exist without it (and it's the first thing a user would create), then do passwords as they depend on the vaults (I would say passwords are "under" the vault), then once you do them, you can start working on tags then categories, and so on...

See more

I have a project (in production) that a part of it is generating HTML from JSON object normally we use Microsoft SQL Server only as our main database. but when it comes to this part some team members suggest working with a NoSQL database as we are going to handle JSON data for both retrieval and querying. others replied that will add complexity and we will lose SQL Servers' Unit Of Work which will break the Atomic behavior, and they suggest to continue working with SQL Server since it supports working with JSON. If you have practical experience using JSON with SQL Server, kindly share your feedback.

See more
Replies (2)
TwoBySea

I agree with the advice you have been given to stick with SQL Server. If you are on the latest SQL Server version you can query inside the JSON field. You should set up a test database with a JSON field and try some queries. Once you understand it and can demonstrate it, show it to the other developers that are suggesting MongoDB. Once they see it working with their own eyes they may drop their position of Mongo over SQL. I would only seriously consider MongoDB if there was no other SQL requirements. I wouldn't do both. I'd be all SQL or all Mongo.

See more
Kevin Deyne
Principal Software Engineer at Accurate Background · | 2 upvotes · 50.5K views
Recommends

I think the key thing to look for is what kind of queries you're expecting to do on that JSON and how stable that data is going to be. (And if you actually need to store the data as JSON; it's generally pretty inexpensive to generate a JSON object)

MongoDB gets rid of the relational aspect of data in favor of data being very fluid in structure.

So if your JSON is going to vary a lot/is unpredictable/will change over time and you need to run queries efficiently like 'records where the field x exists and its value is higher than 3', that's a great use case for MongoDB.

It's hard to solve this in a standard relational model: Indexing on a single column that has wildly different values is pretty much impossible to do efficiently; and pulling out the data in its own columns is hard because it's hard to predict how many columns you'd have or what their datatypes would be. If this sounds like your predicament, 100% go for MongoDB.

If this is always going to be more or less the same JSON and the fields are going to be predictably the same, then the fact that it's JSON doesn't particularly matter much. Your indexes are going to approach it similar to a long string.

If the queried fields are very predictable, you should probably consider storing the fields as separate columns to have better querying capabilities. Ie if you have {"x":1, "y":2}, {"x":5, "y":6}, {"x":9, "y":0} - just make a table with an x and y column and generate the JSON. The CPU hit is worth it compared to the querying capabilities.

See more
Needs advice
on
FirebaseFirebaseMongoDBMongoDB
and
MySQLMySQL

Hey everyone, My users love Microsoft Excel, and so do I. I've been making tools for them in the form of workbooks for years, these tools usually have databases included in the spreadsheets or communicate to free APIs around the web, but now I want to distribute these tools in the form of Excel Add-ins for several reasons.

I want these Add-ins to communicate to a personal server to authorize users, read from my databases, and write to them while they're using their Excel environment. I have never built a website, so what would be a good solution for this, considering I'm new to all of these technologies? I know about the existence of Microsoft Azure, Microsoft SharePoint, and Google Sheets, but I don't know how to feel about those.

See more
Replies (2)

Just definitely don't use firebase. All of MongoDB, MySQL, MariaDB and PostGreSQL have a lot of community support and history.

See more
Recommends
on
SnowflakeSnowflake

Snowflake is a NoSQL database in the cloud, which also accepts SQL calls. Users can obtain an ODBC driver for SnowFlake, which would allow your Excel apps to write/read from the backend, locally.

See more
Ilias Mentzelos
Software Engineer at Plum Fintech · | 9 upvotes · 243.8K views
Needs advice
on
CouchbaseCouchbase
and
MongoDBMongoDB

Hey, we want to build a referral campaign mechanism that will probably contain millions of records within the next few years. We want fast read access based on IDs or some indexes, and isolation is crucial as some listeners will try to update the same document at the same time. What's your suggestion between Couchbase and MongoDB? Thanks!

See more
Replies (2)
Jon Clarke
Enterprise Account Exec at ScyllaDB · | 4 upvotes · 88.6K views
Recommends
on
CouchbaseCouchbaseScyllaDBScyllaDB

I am biased (work for Scylla) but it sounds like a KV/wide column would be better in this use case. Document/schema free/lite DBs data stores are easier to get up and running on but are not as scalable (generally) as NoSQL flavors that require a more rigid data model like ScyllaDB. If your data volumes are going to be 10s of TB and transactions per sec 10s of 1000s (or more), look at Scylla. We have something called lightweight transactions (LWT) that can get you consistency.

See more
Recommends
on
MongoDBMongoDB

I have found MongoDB highly consistent and highly available. It suits your needs. We usually trade off partion tolerance fot this. Having said that, I am little biased in recommendation as I haven't had much experience with couchbase on production.

See more
Needs advice
on
MongoDBMongoDBMySQLMySQL
and
PostgreSQLPostgreSQL

I'm planning to build a freelance marketplace website, using tools like Next.js, Firebase Authentication, Node.js, but I need to know which type of database is suitable with performance and powerful features. I'm trying to figure out what the best stack is for this project. If anyone has advice please, I’d love to hear more details. Thanks.

See more
Replies (3)
Reza Malek
at Meam Software Engineering Group · | 9 upvotes · 188.2K views
Recommends
on
PostgreSQLPostgreSQL

Postgres and MySQL are very similar, but Mongo has differences in terms of storage type and the CAP theorem. For your requirement, I prefer Postgres (or MySQL) over MongoDB. Mongo gives you no schema which is not always good. on the other hand, it is more common in NodeJS community, so you may find more articles about Node-Mongo stuff. I suggest to stay with RDBMS if possible.

See more
Recommends
on
MySQLMySQLPostgreSQLPostgreSQL

This is a little about experience. Postgresql is fine. You can use either the related table structure or the json table structure.

See more
Ruslan Rayanov
Recommends
on
MySQLMySQL

We have a ready-made engine for the online exchange and marketplace. To customize it, you only need to know sql. Connecting any database is not a problem. https://falconspace.site/list/solutions

See more
Dennis Kraaijeveld
Needs advice
on
ExpressJSExpressJSMongoDBMongoDB
and
PostgreSQLPostgreSQL

For learning purposes, I am trying to design a dashboard that displays the total revenue from all connected webshops/marketplaces, displaying incoming orders, total orders, etc.

So I will need to get the data (using Node backend) from the Shopify and marketplace APIs, storing this in the database, and get the data from the back end.

My question is:

What kind of database should I use? Is MongoDB fine for storing this kind of data? Or should I go with a SQL database?

See more
Replies (3)
Arash JalaliGhalibaf
Software Engineer at Cafe Bazaar · | 10 upvotes · 252.7K views
Recommends
on
PostgreSQLPostgreSQL

Postgres is a solid database with a promising background. In the relational side of database design, I see Postgres as an absolute; Now the arguments and conflicts come in when talking about NoSQL data types. The truth is jsonb in Postgres is efficient and gives a good performance and storage. In a comparison with MongoDB with the same resources (such as RAM and CPU) with better tools and community, I think you should go for Postgres and use jsonb for some of the data. All in all, don't use a NoSQL database just cause you have the data type matching this tech, have both SQL and NoSQL at the same time.

See more
Recommends
on
MongoDBMongoDB

I have found MongoDB easier to work with. Postgres and SQL in general, in my experience, is harder to work with. While Postgres does provide data consistency, MongoDB provides flexibility. I've found the MongoDB ecosystem to be really great with a good community. I've worked with MongoDB in production and it's been great. I really like the aggregation system and using query operators such as $in, $pull, $push.

While my opinion may be unpopular, I have found MongoDB really great for relational data, using aggregations from a code perspective. In general, data types are also more flexible with MongoDB.

See more
Luciano Bustos
Senior Software Developer · | 1 upvotes · 242.5K views
Recommends
on
PostgreSQLPostgreSQL

I will use PostgreSQL because you have more powerfull feature for data agregation and views (the raw data from shopify and others could be stored as is) and then use views to produce diff. kind of reports unless you wanna create those aggregations/views in nodejs code. HTH

See more
Krunal Shah
Technical Lead at Infynno Solutions · | 7 upvotes · 265.1K views
Needs advice
on
MongoDBMongoDB
and
PostgreSQLPostgreSQL

I want to store the data retrieved from multiple APIs and perform some analytics on it. The data stored in DB will never/hardly change. First, I thought it would be better to retrieve the data and create table columns for them, but some data might have different columns than others. So I thought about storing the JSON response from API directly to the table and use it. So which database will be the better choice, PostgreSQL or MongoDB.

See more
Replies (6)
Nikhil Gurnani
Sr. Backend Engineer at Grappus · | 8 upvotes · 257.4K views
Recommends
on
MongoDBMongoDB

Hey Krunal, your requirement sounds pretty clear and specific to what you want to do with that data. My recommendation to you, would be to use MongoDB. Since schema-less IO is faster in MongoDB, your general speed of reading / writing from and to the database would be quick. Additionally, the aggregate framework is very powerful with large data so that is also something that you can use in computing your analytics.

See more
Maxim Ryakhovskiy
Recommends
on
MongoDBMongoDBMongooseMongoose

I suggest you to go with MongoDB, because it is schema-less, i.e., it permits you to easily manipulate the schema of a table. If you want to add a column, it can be done without much effort. Moreover, MongoDB can deal with more types of data, since the latest is stored as key-value pair. I do not what kind of analysis you are going to do, but NoSQL is not the best choice if you are going to use complex queries. In addition, if you are working with huge amount of data and you are interested in optimising the performance, I suggest you PostgreSQL. Since you are speaking about API and JSON, I guess that you may using Node JS for fetching API. I suggest you to try Mongoose, which facilitate the use of MongoDB with Node JS.

See more
Tarun Batra
Senior Software Developer at Okta · | 3 upvotes · 253.4K views
Recommends
on
MongoDBMongoDBPostgreSQLPostgreSQL

Looks like the use case is to store JSON data. mongoDB and Postgres differ in so many aspects like scaling and consistency. Postgres has excellent JSON support now with the power of SQL. MongoDB is good in handling schema less data. However in this case it seems these differences don’t matter that much. I’d recommend you go with what you are most comfortable with.

See more
Luiz H. Rapatão
Staff Software Engineer at rapatao.com · | 3 upvotes · 253.4K views
Recommends
on
MongoDBMongoDB

I don't have an unquestionable opinion regarding your use case. I only trend to pick the MongoDB since it is schemaless avoiding null columns that you not always know when it is used (it depends on the source of the data). The only drawback that I could consider is the query's complexity in MongoDB, sometimes it is a bit tricky, when compared to the traditional SQL queries.

See more
Bob Bass
President & Full Stack Enginee at Narro, LLC · | 3 upvotes · 253.3K views
Recommends
on
MySQLMySQLPostgreSQLPostgreSQL

This is largely a matter of opinion. I see that someone else responded and recommended MongoDB but since you are doing data analytics, I highly recommend you go with SQL. You're going to have a really hard time normalizing the data when you can't manipulate relationships and bulk edit with a nice update query.

I'm much more experienced with MySQL than any other database and I am having a hard time getting on board with noSQL entirely because it's really hard to query complex data with relationships using noSQL. I'm using Firestore with one of my apps and MongoDB with another app but they both use MySQL for the heavy lifting and then a document database for things like permissions, caching, etc.

It sounds like the type of problem you need to reverse engineer. I'm sure you can imagine what the data sets would look like if you use MongoDB or Postgres. I suspect that putting in a little bit more work up front will pay high dividends and productivity once the data is normalized.

Again - it's largely a matter of preference but I prefer SQL almost every time.

See more
Recommends
on
MongoDBMongoDB

MongoDB should be better for unstructured/less structured data.

See more
Decisions about MongoDB and SQLite
Micha Mailänder
CEO & Co-Founder at Dechea · | 14 upvotes · 86.1K views

Fauna is a serverless database where you store data as JSON. Also, you have build in a HTTP GraphQL interface with a full authentication & authorization layer. That means you can skip your Backend and call it directly from the Frontend. With the power, that you can write data transformation function within Fauna with her own language called FQL, we're getting a blazing fast application.

Also, Fauna takes care about scaling and backups (All data are sharded on three different locations on the globe). That means we can fully focus on writing business logic and don't have to worry anymore about infrastructure.

See more

I’m newbie I was developing a pouchdb and couchdb app cause if the sync. Lots of learning very little code available. I dropped the project cause it consumed my life. Yeats later I’m back into it. I researched other db and came across rethinkdb and mongo for the subscription features. With socketio I should be able to create and similar sync feature. Attempted to use mongo. I attempted to use rethink. Rethink for the win. Super clear l. I had it running in minutes on my local machine and I believe it’s supposed to scale easy. Mongo wasn’t as easy and there free online db is so slow what’s the point. Very easy to find mongo code examples and use rethink code in its place. I wish I went this route years ago. All that corporate google Amazon crap get bent. The reason they have so much power in the world is cause you guys are giving it to them.

See more

We started using PostgreSQL because there's no need to upgrade to an enterprise plan to access certain essential features. Postgres is essentially plug-and-play; you download it, install it, and there you go!

Another benefit of using Postgres is that you get to use SQL (Structured Query Language)—which isn't for everyone, but I enjoy how flexible and versatile it is.

Postgres also has point-in-time recovery, which you can export wherever you want—This means you can restore data from any given point in time. With this in mind, if you delete something accidentally, you can go back in time and grab said data without restoring the whole database.

Not to mention Postgres is remarkably fast with several thorough benchmarks comparing it to MongoDB, where Postgres mostly came out on top.

See more

All the benefits of relational joins and constraints, with JSON field types in Postgres to allow for flexibility like mongo. Objection ORM makes query building seamless and abstracts away a lot of complexity of SQL queries.

MongoDB tends to get slow with scale and requires a lot of code to maintain consistency across collections as foreign keys and other constraints are harder to implement. PostgreSQL also has a vibrant community with battle tested stability and horizontal scalability when needed.

See more
Usman Sadiq
Student at University of Toronto · | 8 upvotes · 124.7K views
Migrated
from
PostgreSQLPostgreSQL
to
MongoDBMongoDB

MongoDB's document-oriented paradigm is nicely suited to the results of our ML model. We felt that this compatibility offered some time savings on figuring out and implementing an extensive data formatting and processing system. MongoDB's flexible schemas schemas (due to it being non-relational) were also attractive as a source of additional agility for our development process. The MongoDB ecosystem also has great GUI tools to simplify testing.

See more

Backend:

  • Considering that our main app functionality involves data processing, we chose Python as the programming language because it offers many powerful math libraries for data-related tasks. We will use Flask for the server due to its good integration with Python. We will use a relational database because it has good performance and we are mostly dealing with CSV files that have a fixed structure. We originally chose SQLite, but after realizing the limitations of file-based databases, we decided to switch to PostgreSQL, which has better compatibility with our hosting service, Heroku.
See more
Sergey Rodovinsky

At Pushnami we were looking at several alternative databases that would support following architectural requirements: - very quick prototyping for an unknown domain - ability to support large amounts of data - native ability to replicate and fail over - full stack approach for Node.js development After careful consideration MongoDB came on top, and 3 years later we are still very happy with that decision. Currently we keep almost 2TB of data in our cluster, and start thinking about sharding.

See more
Gabriel Pa

After using couchbase for over 4 years, we migrated to MongoDB and that was the best decision ever! I'm very disappointed with Couchbase's technical performance. Even though we received enterprise support and were a listed Couchbase Partner, the experience was horrible. With every contact, the sales team was trying to get me on a $7k+ license for access to features all other open source NoSQL databases get for free.

Here's why you should not use Couchbase

Full-text search Queries The full-text search often returns a different number of results if you run the same query multiple types

N1QL queries Configuring the indexes correctly is next to impossible. It's poorly documented and nobody seems to know what to do, even the Couchbase support engineers have no clue what they are doing.

Community support I posted several problems on the forum and I never once received a useful answer

Enterprise support It's very expensive. $7k+. The team constantly tried to get me to buy even though the community edition wasn't working great

Autonomous Operator It's actually just a poorly configured Kubernetes role that no matter what I did, I couldn't get it to work. The support team was useless. Same lack of documentation. If you do get it to work, you need 6 servers at least to meet their minimum requirements.

Couchbase cloud Typical for Couchbase, the user experience is awful and I could never get it to work.

Minimum requirements The minimum requirements in production are 6 servers. On AWS the calculated monthly cost would be ~$600. We achieved better performance using a $16 MongoDB instance on the Mongo Atlas Cloud

writing queries is a nightmare While N1QL is similar to SQL and it's easier to write because of the familiarity, that isn't entirely true. The "smart index" that Couchbase advertises is not smart at all. Creating an index with 5 fields, and only using 4 of them won't result in Couchbase using the same index, so you have to create a new one.

Couchbase UI The UI that comes with every database deployment is full of bugs, barely functional and the developer experience is poor. When I asked Couchbase about it, they basically said they don't care because real developers use SQL directly from code

Consumes too much RAM Couchbase is shipped with a smaller Memcached instance to handle the in-memory cache. Memcached ends up using 8 GB of RAM for 5000 documents! I'm not kidding! We had less than 5000 docs on a Couchbase instance and less than 20 indexes and RAM consumption was always over 8 GB

Memory allocations are useless I asked the Couchbase team a question: If a bucket has 1 GB allocated, what happens when I have more than 1GB stored? Does it overflow? Does it cache somewhere? Do I get an error? I always received the same answer: If you buy the Couchbase enterprise then we can guide you.

See more
Omran Jamal
CTO & Co-founder at Bonton Connect · | 5 upvotes · 557.1K views

We actually use both Mongo and SQL databases in production. Mongo excels in both speed and developer friendliness when it comes to geospatial data and queries on the geospatial data, but we also like ACID compliance hence most of our other data (except on-site logs) are stored in a SQL Database (MariaDB for now)

See more
Kyle Harrison
Web Application Developer at Fortinet · | 11 upvotes · 980.3K views

MySQL has a lot of strengths working for it. It's simple and easy to set up and use. It's JSON engine is also really good these days. Mongo is also simple to setup and use, and it's speed as a document-object storage engine is first class.

Where Postgres has both beat is in it's combining of all of the features that make both MySQL and Mongo great, while adding on enterprise grade level scalability and replication. It's Postgres' stability and robustness, while still fulfilling the roles of it's contemporaries extremely well that edge Postgre for me.

See more
Manage your open source components, licenses, and vulnerabilities
Learn More
Pros of MongoDB
Pros of SQLite
  • 828
    Document-oriented storage
  • 593
    No sql
  • 553
    Ease of use
  • 464
    Fast
  • 410
    High performance
  • 255
    Free
  • 218
    Open source
  • 180
    Flexible
  • 145
    Replication & high availability
  • 112
    Easy to maintain
  • 42
    Querying
  • 39
    Easy scalability
  • 38
    Auto-sharding
  • 37
    High availability
  • 31
    Map/reduce
  • 27
    Document database
  • 25
    Easy setup
  • 25
    Full index support
  • 16
    Reliable
  • 15
    Fast in-place updates
  • 14
    Agile programming, flexible, fast
  • 12
    No database migrations
  • 8
    Easy integration with Node.Js
  • 8
    Enterprise
  • 6
    Enterprise Support
  • 5
    Great NoSQL DB
  • 4
    Support for many languages through different drivers
  • 3
    Schemaless
  • 3
    Aggregation Framework
  • 3
    Drivers support is good
  • 2
    Fast
  • 2
    Managed service
  • 2
    Easy to Scale
  • 2
    Awesome
  • 2
    Consistent
  • 1
    Good GUI
  • 1
    Acid Compliant
  • 163
    Lightweight
  • 135
    Portable
  • 122
    Simple
  • 81
    Sql
  • 29
    Preinstalled on iOS and Android
  • 2
    Free
  • 2
    Tcl integration
  • 1
    Portable A database on my USB 'love it'

Sign up to add or upvote prosMake informed product decisions

Cons of MongoDB
Cons of SQLite
  • 6
    Very slowly for connected models that require joins
  • 3
    Not acid compliant
  • 2
    Proprietary query language
  • 2
    Not for multi-process of multithreaded apps
  • 1
    Needs different binaries for each platform

Sign up to add or upvote consMake informed product decisions

- No public GitHub repository available -

What is MongoDB?

MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.

What is SQLite?

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Need advice about which tool to choose?Ask the StackShare community!

What companies use MongoDB?
What companies use SQLite?
Manage your open source components, licenses, and vulnerabilities
Learn More

Sign up to get full access to all the companiesMake informed product decisions

What tools integrate with MongoDB?
What tools integrate with SQLite?

Sign up to get full access to all the tool integrationsMake informed product decisions

Blog Posts

Dec 8 2020 at 5:50PM

DigitalOcean

GitHubMySQLPostgreSQL+11
3
2448
JavaScriptGitHubNode.js+29
14
13637
GitGitHubDocker+34
29
42694
GitGitHubSlack+30
27
18693
What are some alternatives to MongoDB and SQLite?
Amazon DynamoDB
With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
MySQL
The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
PostgreSQL
PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
Cassandra
Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
See all alternatives