Amazon Redshift vs Postico

Overview

Amazon Redshift

Stacks1.5K

Followers1.4K

Votes108

Postico

Stacks69

Followers101

Votes12

Amazon Redshift vs Postico: What are the differences?

Pricing Model: Amazon Redshift follows a pay-as-you-go pricing model based on the type and number of nodes used, while Postico is a one-time purchase with no ongoing subscription fees. This difference in pricing models can significantly impact the total cost of ownership for users over time.
Scalability: Amazon Redshift is designed to scale effortlessly from a few hundred gigabytes to a petabyte or more, making it suitable for organizations with large volumes of data. In contrast, Postico is more focused on providing an intuitive interface for working with PostgreSQL databases, without the same level of scalability as Amazon Redshift.
Data Storage: Amazon Redshift stores data in a columnar format, which is optimized for analytical queries on large datasets. On the other hand, Postico stores data in a traditional row-based format, which may impact the performance of complex analytical queries compared to Amazon Redshift.
Query Performance: Amazon Redshift is optimized for performance with parallel processing capabilities, allowing it to handle complex queries efficiently. Postico, while capable of running SQL queries, may not offer the same level of performance optimization as Amazon Redshift for large-scale data analysis.
Management and Maintenance: Amazon Redshift is a fully managed service, which means that AWS takes care of the infrastructure maintenance, backups, and scaling for users. Postico, being a client tool, requires users to handle the management and maintenance of their PostgreSQL databases independently. This difference in management can impact the resource allocation and technical expertise required from users.
Accessibility and Ease of Use: Postico provides a user-friendly interface for interacting with PostgreSQL databases, making it suitable for developers and data analysts who prefer a more straightforward tool for writing queries and analyzing data. Amazon Redshift, while powerful, may have a steeper learning curve due to its scale and complexity, making it more suitable for users with specialized data warehousing needs.

In Summary, Amazon Redshift and Postico offer distinct features and capabilities, with the former excelling in scalability, performance, and managed services, while the latter provides an intuitive interface for PostgreSQL database management and query writing.

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Advice on Amazon Redshift, Postico

datocrats-org

Jul 29, 2020

Needs adviceon

Amazon EC2

Tableau

PowerBI

We need to perform ETL from several databases into a data warehouse or data lake. We want to

keep raw and transformed data available to users to draft their own queries efficiently
give users the ability to give custom permissions and SSO
move between open-source on-premises development and cloud-based production environments

We want to use inexpensive Amazon EC2 instances only on medium-sized data set 16GB to 32GB feeding into Tableau Server or PowerBI for reporting and data analysis purposes.

319k views319k

Comments

Julien

CTO at Hawk

Sep 19, 2020

Decided

Cloud Data-warehouse is the centerpiece of modern Data platform. The choice of the most suitable solution is therefore fundamental.

Our benchmark was conducted over BigQuery and Snowflake. These solutions seem to match our goals but they have very different approaches.

BigQuery is notably the only 100% serverless cloud data-warehouse, which requires absolutely NO maintenance: no re-clustering, no compression, no index optimization, no storage management, no performance management. Snowflake requires to set up (paid) reclustering processes, to manage the performance allocated to each profile, etc. We can also mention Redshift, which we have eliminated because this technology requires even more ops operation.

BigQuery can therefore be set up with almost zero cost of human resources. Its on-demand pricing is particularly adapted to small workloads. 0 cost when the solution is not used, only pay for the query you're running. But quickly the use of slots (with monthly or per-minute commitment) will drastically reduce the cost of use. We've reduced by 10 the cost of our nightly batches by using flex slots.

Finally, a major advantage of BigQuery is its almost perfect integration with Google Cloud Platform services: Cloud functions, Dataflow, Data Studio, etc.

BigQuery is still evolving very quickly. The next milestone, BigQuery Omni, will allow to run queries over data stored in an external Cloud platform (Amazon S3 for example). It will be a major breakthrough in the history of cloud data-warehouses. Omni will compensate a weakness of BigQuery: transferring data in near real time from S3 to BQ is not easy today. It was even simpler to implement via Snowflake's Snowpipe solution.

We also plan to use the Machine Learning features built into BigQuery to accelerate our deployment of Data-Science-based projects. An opportunity only offered by the BigQuery solution

193k views193k

Comments

Detailed Comparison

Amazon Redshift	Postico
It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.	Postico provides an easy to use interface, making Postgres more accessible for newcomers and specialists alike. Postico will look familiar to anyone who has used a Mac before. Just connect to a database and begin working with tables and views. Start with the basics and learn about advanced features of PostgreSQL as you go along.
Optimized for Data Warehousing- It uses columnar storage, data compression, and zone maps to reduce the amount of IO needed to perform queries. Redshift has a massively parallel processing (MPP) architecture, parallelizing and distributing SQL operations to take advantage of all available resources.;Scalable- With a few clicks of the AWS Management Console or a simple API call, you can easily scale the number of nodes in your data warehouse up or down as your performance or capacity needs change.;No Up-Front Costs- You pay only for the resources you provision. You can choose On-Demand pricing with no up-front costs or long-term commitments, or obtain significantly discounted rates with Reserved Instance pricing.;Fault Tolerant- Amazon Redshift has multiple features that enhance the reliability of your data warehouse cluster. All data written to a node in your cluster is automatically replicated to other nodes within the cluster and all data is continuously backed up to Amazon S3.;SQL - Amazon Redshift is a SQL data warehouse and uses industry standard ODBC and JDBC connections and Postgres drivers.;Isolation - Amazon Redshift enables you to configure firewall rules to control network access to your data warehouse cluster.;Encryption – With just a couple of parameter settings, you can set up Amazon Redshift to use SSL to secure data in transit and hardware-acccelerated AES-256 encryption for data at rest.<br>	Peek inside your database. Then edit as needed.;Design a database with a sound structure.;Query, Enquire, Investigate.;Native Experience;Vibrant Design, backwards compatible;Secure out of the box;Dependable Customer Support;Optimized for small displays
Statistics
Stacks 1.5K	Stacks 69
Followers 1.4K	Followers 101
Votes 108	Votes 12
Pros & Cons
Pros 41 Data Warehousing 27 Scalable 17 SQL 14 Backed by Amazon 5 Encryption	Pros 4 Very clean, respectable interface 3 Reliable and easy to use 3 Really modern client 2 Increases productivity
Integrations
SQLite MySQL Oracle PL/SQL	PostgreSQL

What are some alternatives to Amazon Redshift, Postico?

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

dbForge Studio for Oracle

It is a powerful integrated development environment (IDE) which helps Oracle SQL developers to increase PL/SQL coding speed, provides versatile data editing tools for managing in-database and external data.

dbForge Studio for PostgreSQL

It is a GUI tool for database development and management. The IDE for PostgreSQL allows users to create, develop, and execute queries, edit and adjust the code to their requirements in a convenient and user-friendly interface.

dbForge Studio for SQL Server

It is a powerful IDE for SQL Server management, administration, development, data reporting and analysis. The tool will help SQL developers to manage databases, version-control database changes in popular source control systems, speed up routine tasks, as well, as to make complex database changes.

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Liquibase

Liquibase is th leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

Sequel Pro

Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

DBeaver

It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc.

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

dbForge SQL Complete

It is an IntelliSense add-in for SQL Server Management Studio, designed to provide the fastest T-SQL query typing ever possible.

Related Comparisons

Amazon Redshift vs Postico: What are the differences?

Pricing Model: Amazon Redshift follows a pay-as-you-go pricing model based on the type and number of nodes used, while Postico is a one-time purchase with no ongoing subscription fees. This difference in pricing models can significantly impact the total cost of ownership for users over time.
Scalability: Amazon Redshift is designed to scale effortlessly from a few hundred gigabytes to a petabyte or more, making it suitable for organizations with large volumes of data. In contrast, Postico is more focused on providing an intuitive interface for working with PostgreSQL databases, without the same level of scalability as Amazon Redshift.
Data Storage: Amazon Redshift stores data in a columnar format, which is optimized for analytical queries on large datasets. On the other hand, Postico stores data in a traditional row-based format, which may impact the performance of complex analytical queries compared to Amazon Redshift.
Query Performance: Amazon Redshift is optimized for performance with parallel processing capabilities, allowing it to handle complex queries efficiently. Postico, while capable of running SQL queries, may not offer the same level of performance optimization as Amazon Redshift for large-scale data analysis.
Management and Maintenance: Amazon Redshift is a fully managed service, which means that AWS takes care of the infrastructure maintenance, backups, and scaling for users. Postico, being a client tool, requires users to handle the management and maintenance of their PostgreSQL databases independently. This difference in management can impact the resource allocation and technical expertise required from users.
Accessibility and Ease of Use: Postico provides a user-friendly interface for interacting with PostgreSQL databases, making it suitable for developers and data analysts who prefer a more straightforward tool for writing queries and analyzing data. Amazon Redshift, while powerful, may have a steeper learning curve due to its scale and complexity, making it more suitable for users with specialized data warehousing needs.

Amazon Redshift vs Postico

Overview