Citus vs Microsoft SQL Server

Overview

Microsoft SQL Server

Stacks21.3K

Followers15.5K

Votes540

Citus

Stacks60

Followers124

Votes11

GitHub Stars12.0K

Forks736

Citus vs Microsoft SQL Server: What are the differences?

Introduction

In the realm of databases, Citus and Microsoft SQL Server stand out as popular options throughout the industry. The following points highlight key differences between the two platforms from various perspectives.

1. Scalability: Citus is known for its horizontal scalability, allowing you to distribute data across multiple nodes effortlessly. On the other hand, while Microsoft SQL Server offers some tools for scalability, the process is more complex and often requires additional hardware or software solutions.

2. Data Sharding: Citus excels in data sharding, providing automatic distribution and replication of data across nodes for improved performance. In contrast, SQL Server requires manual sharding mechanisms, making it more labor-intensive and potentially prone to error.

3. Cloud Support: Citus has seamless integration with cloud platforms like AWS and Azure, enabling easy deployment and management in the cloud environment. In comparison, while SQL Server offers cloud support, it may involve a steeper learning curve and additional configurations.

4. Open Source Nature: Citus is an open-source extension to PostgreSQL, allowing for greater flexibility and customization options. Microsoft SQL Server, while versatile, remains a proprietary software, limiting some development capabilities and extensibility.

5. Licensing Costs: Citus, being open source, is often more cost-effective in terms of licensing fees, especially for large-scale deployments. Meanwhile, Microsoft SQL Server typically incurs licensing costs based on the number of users or CPU cores, potentially escalating expenses for growing databases.

6. Performance Optimization: Citus boasts automatic query parallelization and distributed execution, optimizing performance for complex queries across multiple nodes. In contrast, SQL Server may require manual tuning and indexing strategies to achieve comparable performance enhancements.

In summary, Citus shines in scalability, data sharding, and cloud support as an open-source extension to PostgreSQL, offering cost-effective solutions with enhanced performance optimization. On the other hand, Microsoft SQL Server provides a robust, proprietary platform with scalable tools and comprehensive licensing options.

Share your Stack

Help developers discover the tools you use. Get visibility for your team's tech choices and contribute to the community's knowledge.

View Docs

CLI (Node.js)

Manual

Advice on Microsoft SQL Server, Citus

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

Masked

Jun 29, 2021

Needs advice

There'd be a couple of thousands of customers with a similar data structure and a medium number of transactions per day, but the data volume is pretty high (Each customer has around 1 or 2 GB so it would sum up to roughly 2TB). The usage pattern is both read and write-heavy (writes are mostly made through a Windows app, but read operations are made by the user), and I need the historical data for analysis and aggregation. The data model is not join-heavy as is not join-free. If the solution is fully ACID, the better, but must be Highly Available and Horizontally Scalable.

Also, the budget is not so high, and I'd rather be using a handful (at most 5) of cheap to medium-sized servers (2 CPU cores and 4GB RAM).

7.65k views7.65k

Comments

Detailed Comparison

Microsoft SQL Server	Citus
Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.	It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.
-	Multi-Node Scalable PostgreSQL;Built-in Replication and High Availability;Real-time Reads/Writes On Multiple Nodes;Multi-core Parallel Processing of Queries;Tenant isolation
Statistics
GitHub Stars -	GitHub Stars 12.0K
GitHub Forks -	GitHub Forks 736
Stacks 21.3K	Stacks 60
Followers 15.5K	Followers 124
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 6 Multi-core Parallel Processing 3 Drop-in PostgreSQL replacement 2 Distributed with Auto-Sharding
Integrations
No integrations available	.NET Apache Spark Loggly Java Rails Datadog Logentries Heroku Papertrail PostgreSQL

What are some alternatives to Microsoft SQL Server, Citus?

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.

Related Comparisons

Citus vs Microsoft SQL Server: What are the differences?

Introduction

Citus vs Microsoft SQL Server

Overview