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Redis vs SQLite: What are the differences?

Redis and SQLite are both widely used database systems. Let's explore the key differences between them.

  1. Data Storage Model: Redis is primarily a key-value store, where each data entry is associated with a unique key. It allows for fast retrieval and storage of data, making it suitable for use cases that require high-performance caching or session management. On the other hand, SQLite follows a relational data model, allowing for structured storage of data in tables with relationships between them. This makes it more suitable for applications that require complex data querying and management.

  2. Data Persistence: Redis stores data primarily in memory, which allows for very fast read and write operations. However, this also means that data is not permanently stored and can be lost in the event of a server restart or crash. In contrast, SQLite stores data on disk, ensuring durability and persistence even after system failures.

  3. Scaling: Redis excels at horizontal scaling, allowing for the distribution of data across multiple nodes in a cluster. This makes it highly scalable for high-throughput applications that require large amounts of data processing. SQLite, on the other hand, is typically used as a single-user or embedded database and does not have built-in support for distributed architecture.

  4. Concurrency: Redis is designed to handle concurrent read and write operations efficiently, making it suitable for applications with high levels of concurrency. It achieves this through single-threaded architecture and asynchronous operations. SQLite, on the other hand, uses a multi-threaded model and supports concurrent read operations but requires serialization of write operations, which can impact performance in highly concurrent scenarios.

  5. Querying and Indexing: Redis provides basic querying capabilities through key lookups and support for data structures such as lists, sets, and sorted sets. However, it lacks advanced query features like joins and complex aggregations available in SQL-based databases. SQLite, being a full-fledged SQL-based database, offers advanced querying capabilities, including joins, aggregations, and the ability to create indexes for efficient data retrieval.

  6. Application Ecosystem: Redis is often used as a caching layer or a message broker in modern application architectures, where it complements other databases like MySQL or PostgreSQL. It has excellent support for various programming languages and frameworks, making it easy to integrate into existing applications. SQLite, on the other hand, is often used as an embedded database within applications or as a lightweight, file-based storage option.

In summary, Redis, a fast and in-memory key-value store, excels in caching and real-time data processing scenarios. SQLite, a lightweight embedded database, is well-suited for local storage in mobile applications or small-scale projects where simplicity and portability are priorities.

Advice on Redis and SQLite
Dimelo Waterson
Needs advice
on
MySQLMySQLPostgreSQLPostgreSQL
and
SQLiteSQLite

I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

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Replies (3)
Recommends
on
SQLiteSQLite

You can easily start with SQlite. Really easy to startup since it doesn't require you to install any additional software since is self-contained. It has interfaces in almost any language and also GUIs. Start learning SQL basics and simpler data models and structures. There are many tutorials, also available in the official website. From there you will easily migrate to another database. MySQL could be next, sonce it's easier to learn at first and has more resources available. PostgreSQL is less widespread, more challenging and has the fewer resorces, but once you have some experience with MySQL is really easy to learn as well. All these technologies are really widespread and used accross the industry so you won't make a wrong decision with any of these.

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Stephen Badger | Vital Beats
Senior DevOps Engineer at Vital Beats · | 6 upvotes · 262.8K views

A question you might want to think about is "What kind of experience do I want to gain, by using a DBMS?". If your aim is to have experience with SQL and any related libraries and frameworks for your language of choice (python, I think?), then it kind of doesn't matter too much which you pick so much. As others have said, SQLite would offer you the ability to very easily get started, and would give you a reasonably standard (if a little basic) SQL dialect to work with.

If your aim is actually to have a bit of "operational" experience, in terms of things like what command line tools might be available as standard for the DBMS, understanding how the DBMS handles multiple databases, when to use multiple schemas vs multiple databases, some basic privilege management etc. Then I would recommend PostgreSQL. SQLite's simplicity actually avoids most of these experiences, which is not helpful to you if that is what you hope to learn. MySQL has a few "quirks" to how it manages things like multiple databases, which may lead you to making less good decisions if you tried to take your experience over to different DBMS, especially in bigger enterprise roles. PostgreSQL is kind of a happy middle ground here, with the ability to start PostgreSQL servers via docker or docker-compose making the actual day-to-day management pretty easy, while still giving you experience of the kinds of considerations I have listed above.

At Vital Beats we make use of PostgreSQL, largely because it offers us a happy balance between good management and backup of data, and good standard command line tools, which is essential for us where we are deploying our solutions within Kubernetes / docker, and so more graphical tools are not always appropriate for us. PostgreSQL is also pretty universally supported in terms of language libraries and frameworks, without having to make compromises on how we want to store and layout our data.

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Julien DeFrance
Principal Software Engineer at Tophatter · | 1 upvotes · 254.3K views
Recommends
on
MySQLMySQL

MySQL's very popular, easy to install, is also available as a managed service across most popular cloud offerings. The support/default tooling (such as MySQL Query Workbench) certainly is a little more baked than what you'll find for Postgres.

https://dev.mysql.com/downloads/workbench/

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Needs advice
on
FirebaseFirebaseMySQLMySQL
and
SQLiteSQLite

Hi everyone! I am a high school student, starting a massive project. I'm building a system for a boarding school to be better connected to their students and be more efficient with information. In the meantime, I am developing a website and an android app. What's the best datastore I can use? I need to be able to access student data on the app from the main database and send push notifications. Also feed updates. What's the best approach? What's the best tool I can use to deploy the website and the database? One for testing and prototyping, and an official one... Thanks in advance!!!!

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Replies (3)
Ahmed AlAskalany
Android Developer at Kitab Sawti · | 5 upvotes · 300.9K views
Recommends
on
FirebaseFirebase

Firebase has Android, iOS, and Web SDKs; and a console where you can develop, manage, and monitor all the data and analytics from one place. Firebase real-time database is good for online presence and instant feed updates, while Firebase Firestone is good for user profile and other relational data records. Firebase has a UI SDK which makes it easy to interface with the resources in the project, and with tons of tutorials and starter projects it should be easy to quickly have a decent prototype to iterate upon. Since you said Massive, use their pricing calculator to figure if your expected scale will be covered by the free quota or if you go for the pay-as-you-go that the price is reasonable for your project.

Good luck with the project!

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Paul Whittemore
Developer and Owner at Appurist Software · | 4 upvotes · 301K views
Recommends
on
FirebaseFirebase

It sounds like a server-client relationship (central database) and while SQLite is probably the simplest, note that its performance is probably the worst of the top 20 or so choices you have. It is different from Firebase and MySQL (and most other databases) in that it is embedded in the product, although it could be embedded in your server itself.

MySQL would require a separate MySQL db server, which means either two servers (one for MySQL, and one to provide your specific services to your client app) or both running on a single server machine. There are many alternatives in the same category as MySQL, and a choice of relational databases or document (NoSQL) databases. But architecturally, they are in the same category as MySQL, a separate db server that your application server would get its data from.

Firebase is different yet again, in that it is a service that is already hosted by a company, providing many integrated features such as authentication and storage of user account info. However it does take care of many of the concerns with running a server, such as performance, scalability and management. There are some negatives that you should be aware of though: any investment of time and coding with Firebase is pretty much non-portable, in that you are stuck with Firebase going forward. If you needed to switch to a different service, not only would it be a different API, but it would be a different architecture and much of your coding would need to be discarded. Second, it's owned and run by Google now, so you have a large corporation backing it, but that also means they could decide to discontinue it without any real effect on the Google bottom line. Also some folks would have concerns with storing data on Google servers. That said, I think if you are aware of these in advance, and especially if you are a high school student, that Firebase is a fairly easy winner here. The server is already set up for you, the documentation is very complete and rich, with lots of examples, and Google is not going away. The main concern would be if it really is massive, there could be a rising cost to the service. I suspect though that it is not massive, even if everyone in a school used it. The number of concurrent connections would not be huge (probably not even into the hundreds, even if there are thousands of users).

I'd go with Firebase even though you will need to learn their API, because you'll need to learn something one way or another. SQLite is a bit of a toy database, and MySQL is a real one but you (or someone) would need to manage that server on top of needing to develop the server and client app. With Firebase, much of the server already exists, including a professionally hosted database. There are tons of high-level features provided and initial cost is somewhere between very low and zero.

Part of this is dependent on what language you want to write this in. Javascript for a cross-platform client app (I'd use Vue.js + Vuetify for UI, and provide it as a web app and optionally wrap that with Electron for a desktop app, Apache Cordova for mobile). Server could be Javascript with an Express-based REST API on Node.js, talking to Firebase for services.

If you were a Java developer though, all this goes out the window and I'd recommend a simple Java server with Javalin for REST API, and embedded ObjectDB for database storage (combined into one server). ObjectDB is very very fast and can be separated out into a scalable server if this became truly massive. But you would probably never need to go that far.

All of this is a lot of work. I hope this isn't for something like an assignment. It is in the order of 6 months of work if you know what you're doing, all year if you're learning as you go.

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Michael Maraist
Chief Architect at Pixia Corp · | 2 upvotes · 300.4K views
Recommends
on
RocksDBRocksDB

Don't think you can go wrong with MySQL or postgresql. python+postgres is VERY well supported stack and can do almost anything. Great visualization and administrative tools for both. There are some data-mismatch problems, however.. node.js/python with mongodb is a bit more modern and makes it trivial to "serialize" data with sprinklings of indexes. If you're using go-lang, then RocksDB is a great high-performance data-modeling base (it's not relational how-ever) It's more like a building-block for key-value store. But it's ACID so you CAN build relational systems on top. I've used LevelDB for other projects (Java/C) (similar architecture and works great on android - chrome uses it for it's metadata-storage). Rock/Level can achieve multi-million writes on cheap hardware thanks to it's trade-offs.

I'm very familiar with SQLite.. Personally my least favorite, but it's the most portable database format, and it does support ACID.. I have many gripes, but biggest issue is parallel access (you really need a single process/thread to own the data-model, then use IPC to communicate with your process/thread).. (same could be said for LevelDB, but that's so efficient, it's almost never an issue).

If your'e using Java, then JavaDB/DerbyDB/HSQLDB are EXCELLENT systems.. highly multi-threaded, good stand-alone tools. (embedded or TCP-connected). Perfect for unit-tests. Can use simple dumb portable formats (e.g. text-file containing only inserts) all the way to classic journaled binary B-tree formats to pure-in-memory. Java has a lot of overhead, so this is only really viable if you're already using Java in your project.

For high performance "memsql" is mysql API to a hybrid in-memory index + on-disk column-database (feels like classic SQL to you though). Falls into the mysql-swiss-army-knife tool-kit.

Similarly with in-memory there is "redis".. Absolutely a joy to work with. It too is a specialty swiss army knife. Steer clear of redis for primary data that you can't lose.. while redis does support persisting data, it isn't very efficient and will become the bottleneck. redis is great for micro-queue's, topics, stat-aggregators, message-repositories (password-management systems, where writes are rare so persistance is viable). Plus I love that redis uses a pure-text protocol so I can netcat or telnet directly into it and do stuff.

I've loved cloud-data-stores.. Amazon "DynamoDB" or Google BigTable are awesome!!! Cheap compared to normal hosting fees of an AWS EC2 instance.. You can play all day.. put a terabyte up, then blow it away.. pay for what you play with. It's a very very different data-model though.. They give you a very very few set of tricks that let you do complex data-modeling - and you have to be clever and have enough foresight to not block yourself into a hole (or have customer abuse expensive queries).

Then there's Cassandra/Hadoop (HBase). These are petabyte scale databases (technically so is Dynamo/BigTable). They're incredibly efficient at what they do. And they have a lot of plugins to do almost anything you need. I personally love these the best (and RocksDB/LevelDB are like their infant children offspring). You can run these on your laptop (unlike Amazon/Google engines above). But their discipline is very different than all the other's above.

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Pros of Redis
Pros of SQLite
  • 886
    Performance
  • 542
    Super fast
  • 513
    Ease of use
  • 444
    In-memory cache
  • 324
    Advanced key-value cache
  • 194
    Open source
  • 182
    Easy to deploy
  • 164
    Stable
  • 155
    Free
  • 121
    Fast
  • 42
    High-Performance
  • 40
    High Availability
  • 35
    Data Structures
  • 32
    Very Scalable
  • 24
    Replication
  • 22
    Great community
  • 22
    Pub/Sub
  • 19
    "NoSQL" key-value data store
  • 16
    Hashes
  • 13
    Sets
  • 11
    Sorted Sets
  • 10
    NoSQL
  • 10
    Lists
  • 9
    Async replication
  • 9
    BSD licensed
  • 8
    Bitmaps
  • 8
    Integrates super easy with Sidekiq for Rails background
  • 7
    Keys with a limited time-to-live
  • 7
    Open Source
  • 6
    Lua scripting
  • 6
    Strings
  • 5
    Awesomeness for Free
  • 5
    Hyperloglogs
  • 4
    Transactions
  • 4
    Outstanding performance
  • 4
    Runs server side LUA
  • 4
    LRU eviction of keys
  • 4
    Feature Rich
  • 4
    Written in ANSI C
  • 4
    Networked
  • 3
    Data structure server
  • 3
    Performance & ease of use
  • 2
    Dont save data if no subscribers are found
  • 2
    Automatic failover
  • 2
    Easy to use
  • 2
    Temporarily kept on disk
  • 2
    Scalable
  • 2
    Existing Laravel Integration
  • 2
    Channels concept
  • 2
    Object [key/value] size each 500 MB
  • 2
    Simple
  • 162
    Lightweight
  • 135
    Portable
  • 121
    Simple
  • 80
    Sql
  • 28
    Preinstalled on iOS and Android
  • 2
    Tcl integration
  • 1
    Free
  • 1
    Portable A database on my USB 'love it'

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Cons of Redis
Cons of SQLite
  • 15
    Cannot query objects directly
  • 3
    No secondary indexes for non-numeric data types
  • 1
    No WAL
  • 2
    Not for multi-process of multithreaded apps
  • 1
    Needs different binaries for each platform

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What is Redis?

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

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.

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What are some alternatives to Redis and SQLite?
Memcached
Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
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.
RabbitMQ
RabbitMQ gives your applications a common platform to send and receive messages, and your messages a safe place to live until received.
Hazelcast
With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.
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