Apache Airflow vs AWS Data Pipeline vs Skyvia

Apache Airflow and AWS Data Pipeline both offer a data integration solution. Compare the features and benefits, data sources and destinations, and see which meets your needs. Look at the side-by-side comparison chart of the two data integration solutions.

Look at the side-by-side comparison chart

Apache Airflow

vs

AWS Data Pipeline

vs

Skyvia

About the Services

Apache Airflow

Apache Airflow is a free, open-source platform for developing batch-oriented workflows. It launched in 2014 and has big-name companies like Airbnb, Lyft, and Etsy in its portfolio. It has a growing community of over 2,000 contributors and many users worldwide.

Apache Airflow uses a workflow management system. This system handles automating and monitoring data integration processes. It can handle simple data transfers and complex machine-learning workflows. The user interface is easy to use, so you can focus on your work instead of minding a confusing interface.

But having that simple interface has a caveat. Open-source platforms need technical expertise, and Airflow is no different. You can start with several options to install. If you don’t want to hire experts to do this for you, you need to know about Python and some required libraries and even about Docker Containers for a seamless cloud deployment.

Apache Airflow also doesn’t have a record of privacy and security certifications, but it has security features like role-based access control and encryption. So, your data is safe from prying eyes. It also provides logging and auditing capabilities. So, this will help identify and investigate any security or privacy incidents. Companies with stringent security and privacy requirements trust Apache Airflow. But again, either you need some more technical expertise, or pay for someone who knows how to secure Airflow in your environment.

AWS Data Pipeline

AWS Data Pipeline is a cloud-based data integration service from Amazon. It works well with cloud and on-premise data sources. Amazon launched it in 2012. And since then, it helped thousands of customers move and process data.

But unlike AWS Glue, Data Pipeline is not serverless. It requires an Amazon EC2 instance to perform processing.

AWS Data Pipeline has a web interface to define your data processing workflows. And it requires no coding knowledge. In one place, you can schedule, automate, and track your data workflows. It’s more of a fill-in-the-blanks rather than drag-and-drop.

AWS Data Pipeline is like any other AWS service when it comes to security and privacy. It’s HIPAA eligible and has various certifications, including SOC 1 and PCI DSS. Rest assured that your data is in safe hands.

Skyvia

Skyvia is a no-code cloud data integration platform for many data integration scenarios. It’s an all-rounder tool for ETL, ELT, Reverse ETL, data migration, one-way and bi-directional data sync, workflow automation, and more. Devart launched this fantastic product in 2014 for cloud data integration and backup.

Skyvia offers more than 160 ready-made data connectors. These are available for thousands of free users, including 2000+ paid customers. Big names like Hyundai and General Electric trust Skyvia to process their data. Its easy-to-use, drag-and-drop interface suits both IT professionals and business users. And don’t take our word for it. Listen to G2 reviewers about how easy it is to start and work with it. Data integration experts who used other tools can adapt with little to no help from support.

Skyvia has flexible pricing plans perfect for small startups and large enterprises. So, it makes it applicable to businesses of all sizes. Also, Skyvia’s freemium model allows users to start using it now and then decide if they need to upgrade later.

The safety of your data is also our prime concern. So, we hosted it in Microsoft Azure cloud, providing the best data security and privacy. It complies with a wide set of security standards, including SOC 2, ISO 27001, and many others.

Apache AirflowAWS Data PipelineSkyvia
FocusETL, ELT, and reverse ETLETLData ingestion, ELT, ETL, reverse ETL, data sync, workflow automation.
Skill levelPython coding skills.Low code, no-code solutions.
Coding in various languages.
No-code and easy to use wizard.
Sources80+JDBC-compatible connectors and Amazon ecosystem connectors.160+
DestinationsSupported data sources.Supported data sources.Supported data sources, including databases, data warehouses, cloud apps and flat files.
Database replicationFull or incremental load.Full or incremental load.Full table and incremental via change data capture.
Ability for customers to add new data sourcesYes, by coding.Through AWS SDKs.Yes, by request or using REST API connector.
G2 customer satisfaction4.3 out of 5
71 reviews
4.1 out of 5
24 reviews
4.7 out of 5
167 Reviews
Peer Insights satisfaction-4.7
1 Ratings
4.8
87 Ratings
Developer toolsPython packages/CLI.
Web UI.
AWS Data Pipeline CLI.
AWS Management Console.
REST connector for data sources that have REST API.
Advanced ETL capabilitiesIntegration with other integration tools like Kafka, dbt, Airbyte, and more.AWS SDKs.
Query API.
Visual ETL data pipeline designer with data orchestration capabilities.
Compliance and security certificationsNo official list of certifications.SOC 1/2/3, HIPAA, GDPR
ISO 27001, 27017, and 27018
PCI DSS
HIPAA, GDPR, PCI DSS.
ISO 27001 and SOC 2 (by Azure).
Purchase processDownload and install. Use the free trial and talk to sales.Self-service or sales.
Vendor lock-inNonePay-as-you-go.
No minimum contract term.
Monthly or annual contracts.
PricingCloud-hosted with volume-based pricing.
Self-managed with a customized package.
With a free tier and 14-day trial.
Based on frequencies of preconditions and activities.
With 12 months of free tier.
Volume-based and feature-based pricing. Freemium model allows to start with a free plan.

Connectors

Apache Airflow

Apache Airflow provides 80+ built-in data connectors and provider packages. These connectors will work with various types of data sources. And this includes databases, cloud platforms, and messaging systems. It can also deal with popular APIs, data warehouses, and lakes. Some of the most popular connectors include MySQL and PostgreSQL.

But, if you need one that is not available, you can create your own using Airflow’s API. Additionally, the Airflow community never stops developing and sharing new connectors. So, if your data source is so unique and recent, look for a connector in the community first. But if nobody made one for it yet, prepare to roll up your sleeves and code.

AWS Data Pipeline

AWS Data Pipeline has data connectors for AWS RDS, JDBC data sources, and more. These let you connect to various data sources. Be it databases, cloud platforms, and storage systems. Some of the most popular ones include Amazon S3, Amazon RDS, and Amazon Redshift.

AWS Data Pipeline allows you to connect to other data sources using AWS SDKs. This allows you to connect to any data source with an API or a JDBC driver. With this, you can use Java, .NET, and others.

Skyvia

Skyvia offers more than 160 connectors, and more to come very soon. It supports connectors for CRMs, accounting, email marketing, e-commerce, human resources, marketing automation, payment processing, product management, all major databases and DWH, flat files, and more. It’s also not a problem whether your data is on-premise or in the cloud.

You can access your on-premise data with peace of mind using the Skyvia Agent. It allows you to connect to databases like SQL Server, MySQL, and more using an encrypted connection. You need to download the Skyvia Agent and install it. Then, download a secured key file and place it in the same folder as the Agent. The Agent is like an unbreakable metal door, and you use the key file to open that door to your on-premise data. You can also set it up so that Skyvia can access only the resources you specify and nothing else.

Customers can also leave a request for a new data connector. And Skyvia will prioritize building it without additional payment.

Transformation

Apache Airflow

Apache Airflow provides a flexible way to handle data transformations. Airflow supports a variety of data transformation tasks. This includes data cleansing, aggregation, filtering, and enrichment. You can perform transformations using code-based approaches. So, if you prefer to click than code to perform transformations, this is not for you.

Airflow has a web, graphical interface for data transformations, but coding is always required. So, it supports programming languages like Python and SQL.

AWS Data Pipeline

AWS Data Pipeline supports various types of transformations like filtering, aggregation, and normalization. You can use a simple drag-and-drop interface to perform transformations. Or write your transformations using a programming language like Python or Java. For even more complex transformations, you can also use Hive, Pig, and MapReduce.

Scheduling data transformation activities is easy with AWS Data Pipeline. And you can also check it in real-time using the AWS Management Console or through API calls. With AWS Data Pipeline, customers have complete control over their data transformation process.

Skyvia

Skyvia is a full-featured ETL service that allows powerful data transformations. It is a no-code solution allowing data splitting, conversion, lookups, and many more.

You can use the Skyvia Data Flow and Control Flow for advanced data pipelines. Transformations for these advanced pipelines are flexible. It supports extending your data with new columns, conditional flows, and summarized values. And all these you can do with parameters, variables, and more for flexibility without code.

Moreover, Skyvia has an Expression Builder to build formulas with many functions. With this, you can convert or extract parts of the data or form new values to suit your needs. And if you love coding in SQL, Skyvia can further extend your transformation needs. It supports multiple joins, groupings, CASE expressions, and more in SELECT queries. And you can also use DML commands like INSERT, UPDATE, and DELETE.

Support

Apache Airflow

Airflow has an active and helpful community, and users can access various support channels depending on their needs. Their website provides documentation and guides for all levels of users. They also have a mailing list where users can ask for help and get support from the community.

For those who need more help, premium support is available through third-party vendors. These vendors provide support levels, including response time guarantees and service-level agreements (SLAs). They also offer training and consulting services.

Users can reach out to these vendors through their websites or by contacting them directly to benefit from their premium support services. With these options, users can choose the level of support that fits their needs and budget.

AWS Data Pipeline

AWS Data Pipeline provides various levels of customer support. You can access documentation available on the AWS website. You can also submit tickets through the AWS Support Center. Or engage with the AWS community for guidance and support.

There are 4 plans for premium support: Developer, Business, Enterprise, and Enterprise Plus. The plans differ in the level of support and the services included. It can be any or all of the following:

• 24/7 access to AWS support engineers,
• personalized support,
• and guidance for architecture and best practices.

AWS also provides a Service Level Agreement (SLA) for different response times.

Skyvia

Skyvia offers free email, chat (on the website or in-app), and forum support for all customers. It also provides extensive documentation with lots of tutorials and user guides.

For paid customers, there's also a phone support option and additional support options for Enterprise customers.

Pricing

Apache Airflow

Apache Airflow is an open-source platform, which means it’s free to use. There are no hidden charges or fees to access and use Airflow’s core features.

Moreover, Apache Airflow doesn’t need any upfront payment, subscription, or contract. Users can download, install, and run the software. They can do that on their own hardware or cloud infrastructure. They have full control over their deployment, scaling, and maintenance. This makes it an attractive option for those who want to avoid vendor lock-in.

There are also no user, workflow, or data source limitations in using Airflow. You can experiment, innovate, and collaborate on your pipelines without worries.

But this flexibility needs a lot of skilled work hours. So, if you need a data integration tool that is ready to use from day 1, this may not be an attractive option.

AWS Data Pipeline

AWS Data Pipeline offers a pay-as-you-go pricing model. The frequency of pipeline runs forms the basis of the model. Low-frequency runs are pipelines that run less than once a day. Rates are lower than high-frequency runs, which are pipelines that run once a day or more.

AWS Data Pipeline also offers a Free Trial. This includes 3 low-frequency preconditions and 5 low-frequency activities per month. This is free for 12 months. The Free Trial includes access to all AWS features. So, customers can test out the service and see if it meets their needs.

Skyvia

Skyvia Data Integration is a freemium tool with an option to request a 14-day trial. So, price is not a barrier to entry.

And when you’re ready, paid plans start from $19 per month. Pricing tiers depend on a few factors. It includes the number of loaded records, scheduling frequency, and advanced ETL features. There are no sale commitments. And customers can upgrade or downgrade at any time. Check out a detailed comparison here.

If you doubt the price is worth it, check out review sites like G2. Aside from ease of use, reasonable pricing is one of the things Skyvia customers like. So, you can be sure the features you get are worth every penny.