Software Alternatives, Accelerators & Startups

Brilliant Database VS Amazon Redshift

Compare Brilliant Database VS Amazon Redshift and see what are their differences

Brilliant Database logo Brilliant Database

Create a personal or business desktop database fast and easily using this simple all-in-one database software. Free 30 day trial.

Amazon Redshift logo Amazon Redshift

Learn about Amazon Redshift cloud data warehouse.
  • Brilliant Database Landing page
    Landing page //
    2021-07-24
  • Amazon Redshift Landing page
    Landing page //
    2023-03-14

Brilliant Database features and specs

  • User-Friendly Interface
    Brilliant Database features an intuitive drag-and-drop interface that makes it accessible for users with varying levels of technical expertise.
  • Customization
    The software offers extensive customization options, allowing users to tailor database structures, forms, and reports to their specific needs.
  • Data Security
    Brilliant Database incorporates robust data security measures, including user authentication and access controls, to protect sensitive information.
  • Standalone Application
    The database can be compiled into an independent application, making it easy to distribute and use on different systems without requiring additional software.
  • Scalability
    The platform is scalable, supporting single-user databases as well as multi-user, networked environments.

Possible disadvantages of Brilliant Database

  • Cost
    Brilliant Database can be expensive, especially for small businesses or individual users who may find the pricing prohibitive.
  • Limited Mobile Support
    The software lacks comprehensive mobile support, which can be a drawback for users who need to access their databases on the go.
  • Learning Curve
    While the interface is user-friendly, mastering the full range of features and capabilities may take some time and effort.
  • Limited Integration
    Brilliant Database does not offer robust integration options with other software solutions, potentially limiting its utility in a complex, multi-application environment.
  • Performance
    For very large datasets, performance may degrade, potentially affecting the efficiency of operations and response times.

Amazon Redshift features and specs

  • Scalability
    Amazon Redshift allows you to scale your data warehouse up or down easily based on your needs with just a few clicks or by using the API, providing flexibility to handle varying workloads.
  • Performance
    Redshift uses columnar storage, parallel processing, and efficient data compression techniques to deliver high performance for complex queries and large datasets.
  • Integration
    It seamlessly integrates with various AWS services like S3, DynamoDB, and QuickSight, making it easier to build a comprehensive data ecosystem.
  • Cost-effective
    Redshift offers a pay-as-you-go pricing model with no upfront costs, and you can save more with reserved instances, making it cost-effective for many businesses.
  • Security
    It includes features like encryption, Virtual Private Cloud (VPC), and compliance certifications (such as SOC 1, SOC 2, SOC 3, and more) to ensure data security and compliance.
  • Managed Service
    Amazon Redshift is a fully managed service, so it takes care of managing, monitoring, and scaling the infrastructure, allowing you to focus on your data and insights.

Possible disadvantages of Amazon Redshift

  • Complexity
    Although Redshift is powerful, it can be complex to set up, configure, and optimize for best performance, requiring knowledge and experience in data warehousing.
  • Cost for Unused Resources
    While Redshift is cost-effective for large-scale operations, costs can add up quickly if resources are not managed properly, especially with long-running clusters that are under-utilized.
  • Maintenance Windows
    Despite being a managed service, maintenance windows and updates can occasionally lead to downtime or performance degradation, impacting availability.
  • Data Transfer Costs
    Transferring data in and out of Redshift can incur additional costs, particularly if large volumes of data are involved, which can affect overall budget planning.
  • Vendor Lock-in
    Using Amazon Redshift ties you to the AWS ecosystem, which could be a disadvantage if you are considering a multi-cloud strategy or planning to switch providers in the future.

Brilliant Database videos

How to use Brilliant Database Professional

Amazon Redshift videos

Getting Started with Amazon Redshift - AWS Online Tech Talks

More videos:

  • Review - Amazon Redshift Materialized Views
  • Tutorial - Amazon Redshift Tutorial | Amazon Redshift Architecture | AWS Tutorial For Beginners | Simplilearn

Category Popularity

0-100% (relative to Brilliant Database and Amazon Redshift)
Databases
39 39%
61% 61
NoSQL Databases
100 100%
0% 0
Big Data
0 0%
100% 100
Development
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Brilliant Database and Amazon Redshift

Brilliant Database Reviews

We have no reviews of Brilliant Database yet.
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Amazon Redshift Reviews

Data Warehouse Tools
No, SQL (Structured Query Language) is not a data warehouse itself. SQL is a programming language used for managing and querying data stored in relational database management systems (RDBMS) and data warehouses. Many data warehouse solutions, such as Peliqan, Amazon Redshift, and PostgreSQL, support SQL for querying and analyzing data within the data warehouse
Source: peliqan.io
Top 6 Cloud Data Warehouses in 2023
Coined in November 2021, Amazon Redshift was launched as a fully managed cloud data warehouse that can handle petabyte-scale data. While it was not the first cloud data warehouse, it became the first to proliferate in the market share after a large-scale adoption. Redshift uses SQL dialect based on PostgreSQL, which is well-known by many analysts globally, and its...
Source: geekflare.com
Top 5 Cloud Data Warehouses in 2023
Jan 11, 2023 The 5 best cloud data warehouse solutions in 2023Google BigQuerySource: https://cloud.google.com/bigqueryBest for:Top features:Pros:Cons:Pricing:SnowflakeBest for:Top features:Pros:Cons:Pricing:Amazon RedshiftSource: https://aws.amazon.com/redshift/Best for:Top features:Pros:Cons:Pricing:FireboltSource: https://www.firebolt.io/Best for:Top...
Top 5 BigQuery Alternatives: A Challenge of Complexity
As the most proven tool in this category, Amazon Redshift is a fully managed cloud-based data warehouse used to collect and store data. Like BigQuery, Redshift seamlessly integrates with multiple products and ETL services.
Source: blog.panoply.io

Social recommendations and mentions

Based on our record, Amazon Redshift seems to be more popular. It has been mentiond 29 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Brilliant Database mentions (0)

We have not tracked any mentions of Brilliant Database yet. Tracking of Brilliant Database recommendations started around Mar 2021.

Amazon Redshift mentions (29)

  • How to Pitch Your Boss to Adopt Apache Iceberg?
    If your team is managing large volumes of historical data using platforms like Snowflake, Amazon Redshift, or Google BigQuery, you’ve probably noticed a shift happening in the data engineering world. A new generation of data infrastructure is forming — one that prioritizes openness, interoperability, and cost-efficiency. At the center of that shift is Apache Iceberg. - Source: dev.to / about 1 month ago
  • Everyone Uses Postgres… But Why?
    Postgres can be easily adapted to build highly tailored solutions. For instance, Amazon Redshift can be considered a highly scalable fork of Postgres. It’s a distributed database focusing on OLAP workloads that you can deploy in AWS. - Source: dev.to / 6 months ago
  • From ETL and ELT to Reverse ETL
    With the transition from ETL to ELT, data warehouses have ascended to the role of data custodians, centralizing customer data collected from fragmented systems. This pivotal shift has been enabled by a suite of powerful tools: Fivetran and Airbyte streamline the extraction and loading, DBT handles the transformation, and robust warehousing solutions like Snowflake and Redshift store the data. While traditionally... - Source: dev.to / 8 months ago
  • Choosing Between a Streaming Database and a Stream Processing Framework in Python
    They differ from conventional analytic databases like Snowflake, Redshift, BigQuery, and Oracle in several ways. Conventional databases are batch-oriented, loading data in defined windows like hourly, daily, weekly, and so on. While loading data, conventional databases lock the tables, making the newly loaded data unavailable until the batch load is fully completed. Streaming databases continuously receive new... - Source: dev.to / over 1 year ago
  • Choosing the Right AWS Database: A Guide for Modern Applications
    Data warehousing is the process of storing and analyzing large volumes of data for business intelligence and analytics purposes. AWS offers a fully managed data warehousing service called Amazon Redshift that can handle petabyte-scale data warehouses with ease. - Source: dev.to / over 1 year ago
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What are some alternatives?

When comparing Brilliant Database and Amazon Redshift, you can also consider the following products

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Google BigQuery - A fully managed data warehouse for large-scale data analytics.

Microsoft Office Access - Access is now much more than a way to create desktop databases. It’s an easy-to-use tool for quickly creating browser-based database applications.

Vertica - Vertica is a grid-based, column-oriented database designed to manage large, fast-growing volumes of...

Microsoft SQL Server - Microsoft Azure is an open, flexible, enterprise-grade cloud computing platform. Move faster, do more, and save money with IaaS + PaaS. Try for FREE.

LibreOffice - Base - Base, database, database frontend, LibreOffice, ODF, Open Standards, SQL, ODBC