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MariaDB vs RocksDB: What are the differences?
Data Storage: MariaDB is a relational database management system that uses SQL for querying, while RocksDB is an embeddable persistent key-value store for fast storage needs. MariaDB organizes data in tables with defined relationships, whereas RocksDB stores data in key-value pairs, allowing for efficient retrieval based on keys.
ACID Compliance: MariaDB guarantees ACID (Atomicity, Consistency, Isolation, Durability) compliance for transactions, ensuring data integrity in multi-operation scenarios. RocksDB, on the other hand, prioritizes high write throughput and is optimized for scenarios where ACID compliance is not a priority.
Use Cases: MariaDB is suitable for applications that require complex queries, transactions, and structured data storage, making it ideal for traditional relational database use cases. RocksDB, being a key-value store, shines in scenarios that demand high write throughput and fast retrieval of data, such as caching layers or real-time analytics applications.
Storage Engine: MariaDB supports multiple storage engines like InnoDB, MyRocks, and others, providing flexibility in performance tuning and data storage mechanisms. RocksDB, on the contrary, is a single storage engine designed for high-performance applications that need fast and efficient data storage capabilities.
Memory Usage: MariaDB typically consumes more memory for maintaining indexes, caches, and internal data structures due to its relational nature and various storage engines. RocksDB, being a key-value store optimized for efficiency, tends to be more memory-efficient, making it suitable for environments with limited memory resources.
Community and Support: MariaDB has a larger community and extensive support ecosystem, making it easier to find resources, documentation, and assistance for troubleshooting and optimization. RocksDB, being a more specialized storage engine, may have a smaller community and limited support options compared to MariaDB.
In Summary, MariaDB is a robust relational database management system tailored for complex query and transaction environments, while RocksDB is a high-performance key-value store optimized for fast storage and retrieval needs.
I am researching different querying solutions to handle ~1 trillion records of data (in the realm of a petabyte). The data is mostly textual. I have identified a few options: Milvus, HBase, RocksDB, and Elasticsearch. I was wondering if there is a good way to compare the performance of these options (or if anyone has already done something like this). I want to be able to compare the speed of ingesting and querying textual data from these tools. Does anyone have information on this or know where I can find some? Thanks in advance!
You've probably come to a decision already but for those reading...here are some resources we put together to help people learn more about Milvus and other databases https://zilliz.com/comparison and https://github.com/zilliztech/VectorDBBench. I don't think they include RocksDB or HBase yet (you could could recommend on GitHub) but hopefully they help answer your Elastic Search questions.
Hi all. I am an informatics student, and I need to realise a simple website for my friend. I am planning to realise the website using Node.js and Mongoose, since I have already done a project using these technologies. I also know SQL, and I have used PostgreSQL and MySQL previously.
The website will show a possible travel destination and local transportation. The database is used to store information about traveling, so only admin will manage the content (especially photos). While clients will see the content uploaded by the admin. I am planning to use Mongoose because it is very simple and efficient for this project. Please give me your opinion about this choice.
The use case you are describing would benefit from a self-hosted headless CMS like contentful. You can also go for Strapi with a database of your choice but here you would have to host Strapi and the underlying database (if not using SQLite) yourself. If you want to use Strapi, you can ease your work by using something like PlanetSCaleDB as the backing database for Strapi.
Your requirements seem nothing special. on the other hand, MongoDB is commonly used with Node. you could use Mongo without defining a Schema, does it give you any benefits? Also, note that development speed matters. In most cases RDBMS are the best choice, Learn and use Postgres for life!
MongoDB and Mongoose are commonly used with Node.js and the use case doesn't seem to be requiring any special considerations as of now. However using MongoDB now will allow you to easily expand and modify your use case in future.
If not MongoDB, then my second choice will be PostgreSQL. It's a generic purpose database with jsonb support (if you need it) and lots of resources online. Nobody was fired for choosing PostgreSQL.
SQL is not so good at query lat long out of the box. you might need to use additional tools for that like UTM coordinates or Uber's H3.
If you use mongoDB, it support 2d coordinate query out of the box.
Any database will be a great choice for your app, which is less of a technical challenge and more about great content. Go for it, the geographical search features maybe be actually handy for you.
Hi, Maxim! Most likely, the site is almost ready. But we would like to share our development with you. https://falcon.web-automation.ru/ This is a constructor for web application. With it, you can create almost any site with different roles which have different levels of access to information and different functionality. The platform is managed via sql. knowing sql, you will be able to change the business logic as necessary and during further project maintenance. We will be glad to hear your feedback about the platform.
Any database engine should work well but I vote for Postgres because of PostGIS extension that may be handy for travel related site. There's nothing special about your requirements.
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)
Pros of MariaDB
- Drop-in mysql replacement149
- Great performance100
- Open source74
- Free55
- Easy setup44
- Easy and fast15
- Lead developer is "monty" widenius the founder of mysql14
- Also an aws rds service6
- Consistent and robust4
- Learning curve easy4
- Native JSON Support / Dynamic Columns2
- Real Multi Threaded queries on a table/db1
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1