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  1. Stackups
  2. Application & Data
  3. Relational Databases
  4. Postgresql As A Service
  5. Amazon RDS for PostgreSQL vs Citus

Amazon RDS for PostgreSQL vs Citus

OverviewDecisionsComparisonAlternatives

Overview

Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
Stacks814
Followers607
Votes40
Citus
Citus
Stacks60
Followers124
Votes11
GitHub Stars12.0K
Forks736

Amazon RDS for PostgreSQL vs Citus: What are the differences?

Introduction In this case, we will be discussing the key differences between Amazon RDS for PostgreSQL and Citus. Both Amazon RDS for PostgreSQL and Citus are database platforms that offer different features and functionalities. Understanding the differences between these platforms can help businesses make informed decisions when it comes to selecting the appropriate database solution for their specific needs and requirements.

  1. Scalability and Sharding: One of the key differences between Amazon RDS for PostgreSQL and Citus is their approach to scalability. Amazon RDS for PostgreSQL offers scalability through vertical scaling, allowing users to increase the compute and memory resources of their database instances. On the other hand, Citus leverages horizontal scaling and sharding techniques, splitting the data across multiple nodes to achieve scalability and increased performance.

  2. Performance: When it comes to performance, Citus often outperforms Amazon RDS for PostgreSQL. Citus's distributed architecture allows it to parallelize queries, enabling faster query execution and data retrieval. Additionally, Citus utilizes efficient data distribution mechanisms and indexing techniques that further enhance performance, especially for complex analytical workloads.

  3. Data Partitioning: Data partitioning is handled differently in Amazon RDS for PostgreSQL and Citus. Amazon RDS for PostgreSQL utilizes table partitioning, where tables are divided into smaller partitions based on a specified partition key. On the other hand, Citus offers transparent sharding, where the data is automatically and evenly distributed across multiple nodes based on the shard key. This approach simplifies data partitioning and improves query performance.

  4. Support for Distributed Joins: Another important difference between Amazon RDS for PostgreSQL and Citus is their support for distributed joins. Citus is designed to handle distributed joins efficiently by parallelizing join operations across multiple nodes. In contrast, Amazon RDS for PostgreSQL does not have built-in support for distributed joins, which can impact the performance of queries involving multiple tables.

  5. Management and Monitoring: Amazon RDS for PostgreSQL provides a comprehensive management console and monitoring tools, making it easier to manage and monitor your database instances. It offers features such as automated backups, security patching, and performance monitoring. While Citus can be managed using the same tools as PostgreSQL, it may require additional setup and configuration for monitoring and management.

  6. Data Localization: In terms of data localization, Citus offers the ability to colocate data where it is most needed. By selecting a specific distribution column, data can be stored on nodes that are geographically closer to the users, reducing latency and improving performance. Amazon RDS for PostgreSQL does not provide built-in support for data localization.

In summary, the key differences between Amazon RDS for PostgreSQL and Citus include their scalability approaches, performance capabilities, data partitioning methods, support for distributed joins, management and monitoring tools, and data localization features. Understanding these differences can help businesses choose the appropriate platform based on their specific requirements.

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Advice on Amazon RDS for PostgreSQL, Citus

Lonnie
Lonnie

CEO - Co-founder US, Mexico Binational Tech Start-up Accelerator, Incubator at Framework Science

May 9, 2019

ReviewonAmazon DynamoDBAmazon DynamoDBAmazon RDS for PostgreSQLAmazon RDS for PostgreSQL

We use Amazon RDS for PostgreSQL because RDS and Amazon DynamoDB are two distinct database systems. DynamoDB is NoSQL DB whereas RDS is a relational database on the cloud. The pricing will mainly differ in the type of application you are using and your requirements. For some applications, both DynamoDB and RDS, can serve well, for some it might not. I do not think DynamoDB is cheaper. Right now we are helping Companies in Silicon Valley and in Southern California go SERVERLESS - drastically lowering costs if you are interested in hearing how we go about it.

9.18k views9.18k
Comments
Jorge
Jorge

Jan 15, 2020

Needs advice

Considering moving part of our PostgreSQL database infrastructure to the cloud, however, not quite sure between AWS, Heroku, Azure and Google cloud. Things to consider: The main reason is for backing up and centralize all our data in the cloud. With that in mind the main elements are: -Pricing for storage. -Small team. -No need for high throughput. -Support for docker swarm and Kubernetes.

51.8k views51.8k
Comments

Detailed Comparison

Amazon RDS for PostgreSQL
Amazon RDS for PostgreSQL
Citus
Citus

Amazon RDS manages complex and time-consuming administrative tasks such as PostgreSQL software installation and upgrades, storage management, replication for high availability and back-ups for disaster recovery. With just a few clicks in the AWS Management Console, you can deploy a PostgreSQL database with automatically configured database parameters for optimal performance. Amazon RDS for PostgreSQL database instances can be provisioned with either standard storage or Provisioned IOPS storage. Once provisioned, you can scale from 10GB to 3TB of storage and from 1,000 IOPS to 30,000 IOPS.

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.

Monitoring and Metrics –Amazon RDS provides Amazon CloudWatch metrics for you DB Instance deployments at no additional charge.;DB Event Notifications –Amazon RDS provides Amazon SNS notifications via email or SMS for your DB Instance deployments.;Automatic Software Patching – Amazon RDS will make sure that the PostgreSQL software powering your deployment stays up-to-date with the latest patches.;Automated Backups – Turned on by default, the automated backup feature of Amazon RDS enables point-in-time recovery for your DB Instance.;DB Snapshots – DB Snapshots are user-initiated backups of your DB Instance.;Pre-configured Parameters – Amazon RDS for PostgreSQL deployments are pre-configured with a sensible set of parameters and settings appropriate for the DB Instance class you have selected.;PostGIS;Language Extensions :PL/Perl, PL/pgSQL, PL/Tcl;Full Text Search Dictionaries;Advanced Data Types : HStore, JSON;Core PostgreSQL engine features
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
814
Stacks
60
Followers
607
Followers
124
Votes
40
Votes
11
Pros & Cons
Pros
  • 25
    Easy setup, backup, monitoring
  • 13
    Geospatial support
  • 2
    Master-master replication using Multi-AZ instance
Pros
  • 6
    Multi-core Parallel Processing
  • 3
    Drop-in PostgreSQL replacement
  • 2
    Distributed with Auto-Sharding
Integrations
No integrations available
.NET
.NET
Apache Spark
Apache Spark
Loggly
Loggly
Java
Java
Rails
Rails
Datadog
Datadog
Logentries
Logentries
Heroku
Heroku
Papertrail
Papertrail
PostgreSQL
PostgreSQL

What are some alternatives to Amazon RDS for PostgreSQL, Citus?

MongoDB

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

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

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.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

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

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

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

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

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

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.

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