Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

RocksDB

Stacks141

Followers290

Votes11

GitHub Stars30.9K

Forks6.6K

Microsoft SQL Server vs RocksDB: What are the differences?

Introduction

In this analysis, we will outline the key differences between Microsoft SQL Server and RocksDB to better understand their unique capabilities and strengths in database management.

Storage Model: Microsoft SQL Server utilizes a traditional relational database management system (RDBMS) approach, organizing data into tables with defined relationships. On the other hand, RocksDB is a key-value store that offers high performance and scalability by efficiently storing and retrieving data based on keys.
Use Cases: SQL Server is primarily designed for handling structured data and complex queries in transactional systems or data warehouses. In contrast, RocksDB is better suited for scenarios that require fast and reliable storage and retrieval of key-value pairs, often used in data caching or real-time analytics applications.
Replication and Sharding: When it comes to data replication and sharding, SQL Server offers built-in features for maintaining data consistency and distributing data across multiple servers. RocksDB, on the other hand, relies on external tools and frameworks to achieve similar scalability and fault tolerance.
Programming Interfaces: SQL Server supports SQL queries for data manipulation and retrieval, making it easier for developers familiar with relational databases to work with. RocksDB provides a simpler set of key-value APIs, focusing on performance and low latency for storage operations without the overhead of SQL query processing.
Data Durability: SQL Server ensures data durability through transaction logging and recovery mechanisms, guaranteeing that committed transactions are saved even in the event of a system failure. RocksDB, being an embedded database, offers similar durability features but may require additional configurations for achieving strong consistency in distributed environments.
Community Support and Licensing: Microsoft SQL Server has a large community of users and enterprise support options but may require licensing fees for certain editions. RocksDB, being an open-source project by Facebook, benefits from community contributions and continuous improvements without direct licensing costs, making it a cost-effective option for many developers.

In Summary, Microsoft SQL Server and RocksDB differ in their storage models, use cases, replication strategies, programming interfaces, data durability, and community support, catering to distinct database management needs based on performance, scalability, and licensing considerations.

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Advice on Microsoft SQL Server, RocksDB

Erin

IT Specialist

Mar 10, 2020

Needs adviceon

Microsoft SQL Server

MySQL

PostgreSQL

I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

I need to use either @{MySQL}|tool:1025| or @{PostgreSQL}|tool:1028| on a @{Linux}|tool:10483| based OS. Which would be better for this application?
I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.

668k views668k

Comments

Josip

Senior frontend developer

Aug 31, 2021

Decided

Needed to transform intranet desktop application to the web-based one, as mid-term project. My choice was to use Django/Angular stack - Django since it, in conjunction with Python, enabled rapid development, an Angular since it was stable and enterprise-level framework. Deadlines were somewhat tight since the project to migrate was being developed for several years and had a lot of domain knowledge integrated into it. Definitely was good decision, since deadlines was manageable, juniors were able to enter the project very quickly and we were able to continuously deploy very well.

73.6k views73.6k

Comments

Detailed Comparison

Microsoft SQL Server	RocksDB
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.
-	Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Statistics
GitHub Stars -	GitHub Stars 30.9K
GitHub Forks -	GitHub Forks 6.6K
Stacks 21.3K	Stacks 141
Followers 15.5K	Followers 290
Votes 540	Votes 11
Pros & Cons
Pros 139 Reliable and easy to use 101 High performance 95 Great with .net 65 Works well with .net 56 Easy to maintain Cons 4 Expensive Licensing 2 Microsoft 1 Replication can loose the data 1 Allwayon can loose data in asycronious mode 1 Data pages is only 8k	Pros 5 Very fast 3 Made by Facebook 2 Consistent performance 1 Ability to add logic to the database layer where needed

What are some alternatives to Microsoft SQL Server, RocksDB?

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.

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.

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.

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.

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.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.