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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Airbyte vs Amazon Redshift

Airbyte vs Amazon Redshift

OverviewComparisonAlternatives

Overview

Amazon Redshift
Amazon Redshift
Stacks1.5K
Followers1.4K
Votes108
Airbyte
Airbyte
Stacks105
Followers112
Votes5
GitHub Stars20.0K
Forks4.9K

Airbyte vs Amazon Redshift: What are the differences?

## Introduction

Airbyte and Amazon Redshift are both popular data tools used for data extraction, transformation, and loading. However, they have key differences that set them apart based on their features and capabilities.

1. **Data Integration Approach**: Airbyte is an open-source data integration platform that allows users to replicate data from various sources to a destination of their choice. On the other hand, Amazon Redshift is a fully managed cloud data warehouse that is optimized for high-performance analytics. While Airbyte focuses on data movement and transformation, Amazon Redshift is geared towards data storage and querying capabilities.

2. **Pricing Model**: Airbyte is free to use as it is open-source software, making it a cost-effective solution for small to medium-sized businesses. In contrast, Amazon Redshift operates on a pay-as-you-go pricing model based on the compute nodes and storage capacity used, which can be a more expensive option for organizations with larger data volumes and complex analytics needs.

3. **Scalability**: Amazon Redshift is highly scalable, allowing users to easily resize their clusters to accommodate growing data requirements and query loads. In comparison, while Airbyte can handle data replication at scale, its scalability may be limited by the resources available on the user's infrastructure or cloud environment.

4. **Performance**: Amazon Redshift is known for its high-performance query processing and optimization, making it ideal for complex analytical workloads and data warehousing. On the other hand, Airbyte focuses on data integration tasks and may not offer the same level of query performance and optimization as Amazon Redshift.

5. **Ecosystem Integration**: Amazon Redshift seamlessly integrates with other AWS services such as S3, Glue, and Lambda, providing a comprehensive data ecosystem for users. Airbyte, while offering connections to a wide range of data sources and destinations, may require additional configurations or custom integrations for seamless ecosystem connectivity.

6. **Maintenance and Support**: Amazon Redshift is a fully managed service, handling tasks such as backups, patches, and maintenance, to ensure high availability and reliability. In contrast, Airbyte being open-source software may require more hands-on maintenance and support from users or their IT teams.

## In Summary, Airbyte and Amazon Redshift differ in their approach to data integration, pricing models, scalability, performance, ecosystem integration, and maintenance and support.

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Detailed Comparison

Amazon Redshift
Amazon Redshift
Airbyte
Airbyte

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.

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

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>
Scheduled updates; Manual full refresh; Real-time monitoring; Debugging autonomy; Optional normalized schemas; Full control over the data; Benefit from the long tail of connectors, and adapt them to your needs; Build connectors in the language of your choice, as they run in Docker containers
Statistics
GitHub Stars
-
GitHub Stars
20.0K
GitHub Forks
-
GitHub Forks
4.9K
Stacks
1.5K
Stacks
105
Followers
1.4K
Followers
112
Votes
108
Votes
5
Pros & Cons
Pros
  • 41
    Data Warehousing
  • 27
    Scalable
  • 17
    SQL
  • 14
    Backed by Amazon
  • 5
    Encryption
Pros
  • 1
    Multiple capabilities
  • 1
    Free
  • 1
    Connect Multiple Sources
  • 1
    Change Data Capture
  • 1
    Easy to use
Integrations
SQLite
SQLite
MySQL
MySQL
Oracle PL/SQL
Oracle PL/SQL
Greenhouse
Greenhouse
Google Cloud Platform
Google Cloud Platform
Mixpanel
Mixpanel
Google Analytics
Google Analytics
PostgreSQL
PostgreSQL
MySQL
MySQL
Shopify
Shopify
Amazon EC2
Amazon EC2
Zendesk
Zendesk
Stripe
Stripe

What are some alternatives to Amazon Redshift, Airbyte?

Google BigQuery

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.

Qubole

Qubole

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

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

Snowflake

Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.

Stitch

Stitch

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Cloudera Enterprise

Cloudera Enterprise

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Treasure Data

Treasure Data

Treasure Data's Big Data as-a-Service cloud platform enables data-driven businesses to focus their precious development resources on their applications, not on mundane, time-consuming integration and operational tasks. The Treasure Data Cloud Data Warehouse service offers an affordable, quick-to-implement and easy-to-use big data option that does not require specialized IT resources, making big data analytics available to the mass market.

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