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Amazon Redshift VS Teradata

Compare Amazon Redshift VS Teradata and see what are their differences

Amazon Redshift logo Amazon Redshift

Learn about Amazon Redshift cloud data warehouse.

Teradata logo Teradata

See why Teradata is the world's leading provider of business analytics solutions, data and analytics solutions, and hybrid cloud products and services.
  • Amazon Redshift Landing page
    Landing page //
    2023-03-14
  • Teradata Landing page
    Landing page //
    2023-09-22

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.

Teradata features and specs

  • Scalability
    Teradata excels in handling large volumes of data and can scale both up and out, making it suitable for large enterprises with growing datasets.
  • Performance
    Teradata's architecture allows for high performance through parallel processing, meaning it can handle complex queries quickly and efficiently.
  • Advanced Analytics
    It provides powerful analytics and supports a wide range of analytical functions, enabling users to gain deep insights from their data.
  • Integration
    Teradata integrates well with various data sources, big data technologies, and business intelligence tools, providing a seamless data ecosystem.
  • Security
    Offers robust security features, including encryption and advanced user access controls, ensuring that data is protected.

Possible disadvantages of Teradata

  • Cost
    Teradata can be expensive to implement and maintain, which may not be practical for smaller organizations or those with limited budgets.
  • Complexity
    The platform can be complex to set up and manage, often requiring specialized knowledge and skills, which might necessitate hiring or training staff.
  • Vendor Lock-In
    Once integrated, migrating away from Teradata can be challenging, leading to potential vendor lock-in issues.
  • Resource Intensive
    Running Teradata may require significant hardware and computational resources, which can add to the overall cost and complexity.
  • Limited Flexibility
    Compared to some newer cloud-native solutions, Teradata can be less flexible in adapting to rapidly changing business requirements and technologies.

Analysis of Amazon Redshift

Overall verdict

  • Amazon Redshift is generally considered a good solution for businesses seeking a robust, scalable, and cost-effective data warehousing service within the AWS cloud environment. However, its suitability may vary depending on specific organizational needs and workloads.

Why this product is good

  • Amazon Redshift is a popular data warehousing service within the AWS ecosystem, known for its scalability, ease of integration with other AWS services, and relatively low cost. It provides fast query performance for large datasets and offers features like columnar storage, parallel query execution, and advanced compression. These attributes make it an attractive choice for organizations looking to perform complex analytics and data processing tasks.

Recommended for

  • Organizations already utilizing AWS services and seeking seamless integration.
  • Businesses requiring scalable data warehousing at a competitive price.
  • Data-driven companies looking to perform fast, complex analytics on large datasets.
  • Teams needing flexible management options that can grow with their data storage needs.

Analysis of Teradata

Overall verdict

  • Yes, Teradata is considered a good choice for organizations looking for powerful data analytics and warehousing solutions. Its long-standing reputation, industry presence, and comprehensive suite of tools make it a valuable option for companies needing scalable and efficient data management solutions.

Why this product is good

  • Teradata is a widely recognized and long-standing player in the data warehousing and analytics industry. It is known for its high-performance analytics capabilities and ability to handle large volumes of data. Teradata products and services are designed to help organizations leverage data to gain insights and drive business outcomes. Their solutions are robust, scalable, and come with a range of tools for data integration, analytics, and management, making them suitable for large enterprises with substantial data needs.

Recommended for

    Teradata is best recommended for large enterprises and organizations that require sophisticated data analytics capabilities, have significant data processing needs, and need solutions that can scale with their business. Industries such as finance, retail, telecommunications, and manufacturing might find Teradata particularly beneficial due to its ability to handle complex queries and large datasets efficiently.

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

Teradata videos

TechBytes: Teradata Vantage

More videos:

  • Review - Teradata Company Profile

Category Popularity

0-100% (relative to Amazon Redshift and Teradata)
Databases
76 76%
24% 24
Tool
0 0%
100% 100
Big Data
100 100%
0% 0
Data Management
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 Amazon Redshift and Teradata

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

Teradata Reviews

Data Warehouse Tools
Teradata: Known for its high cost, Teradata requires contacting the vendor for a quote based on your specific needs. Expect a significant upfront investment.
Source: peliqan.io
16 Top Big Data Analytics Tools You Should Know About
Teradata is one of the most popular Relational Database Management System (RDBMS) developed by the company named Teradata itself.

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.

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 2 months 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 / 7 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
View more

Teradata mentions (0)

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

What are some alternatives?

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

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

Datomic - The fully transactional, cloud-ready, distributed database

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.

Datahike - A durable datalog database adaptable for distribution.

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

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server