About the Services
Azure Data Factory
Azure Data Factory (ADF) is a cloud-based data integration tool from Microsoft. It launched in 2015. And now, it’s popular among enterprises and individuals alike.
ADF offers a wide range of data integration scenarios. This includes ETL, ELT, reverse ETL, data ingestion, replication, and more. You can use over 90 built-in connectors. This covers on-premises and cloud-based data. You can use Azure Data Factory to move data from sources such as SQL Server, Oracle, Salesforce, and SAP. And into destinations such as Azure SQL Database, Azure Blob Storage, and Amazon S3.
Microsoft takes customer data privacy and security very seriously. Microsoft designed Azure Data Factory with several security features. This includes Azure Active Directory integration, role-based access control, data encryption, and more. Moreover, the tool complies with security and privacy standards. This includes GDPR, SOC 1/2, ISO 27001, and HIPAA. This means that you can trust Azure Data Factory to handle your data in a secure and compliant manner.
You can also use ADF by importing SQL Server Integration Services (SSIS) packages.
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 180 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.
 |  |  | |
|---|---|---|---|
| Focus | ETL, ELT, Reverse ETL, streaming. | ETL | Data ingestion, ELT, ETL, reverse ETL, data sync, workflow automation. |
| Skill level | Low-code, no-code solutions. Coding in various languages for complex scenarios. | Low code, no-code solutions. Coding in various languages. | No-code wizard. Top-rated as one of the easiest ETL tools by G2. |
| Sources | 90+ | JDBC-compatible connectors and Amazon ecosystem connectors. | 180+ |
| Destinations | Supported data sources. | Supported data sources. | Supported data sources, including databases, data warehouses, cloud apps and flat files. |
| Database replication | Full and incremental load. | Full or incremental load. | Full table and incremental via change data capture. |
| Ability for customers to add new data sources | Provides SDK for creating custom connectors. | Through AWS SDKs. | Ye s, by request or using REST API connector. |
| G2 customer satisfaction | 4.6 out of 5 57 reviews | 4.1 out of 5 24 reviews | 4.8 out of 5 217 Reviews |
| Peer Insights satisfaction | 4.5 173 Ratings | 4.7 1 Ratings | 4.8 103 Ratings |
| Developer tools | Azure Portal, CLI, and PowerShell. Azure Functions for transformations. Use external services like HDInsight. Visual Studio. | AWS Data Pipeline CLI. AWS Management Console. | REST connector for data sources that have REST API. |
| Advanced ETL capabilities | Importing SSIS packages. Calling External processes from the pipeline. Use Hadoop Streaming. | AWS SDKs. Query API. | Visual ETL data pipeline designer with data orchestration capabilities. |
| Compliance and security certifications | SOC 1/2/3, ISO 27001 / 27017 / 27018, HIPAA, GDPR, CCPA, FedRAMP, Dod SRG, ITAR | 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 process | Self-service through Azure Portal or contacting Microsoft sales. | Use the free trial and talk to sales. | Self-service or sales. |
| Vendor lock-in | Pay-as-you-go or consumption basis. No minimum commitment or contract term. | Pay-as-you-go. No minimum contract term. | Monthly or annual contracts. |
| Pricing | Always Free for 5 low frequency jobs. Included in Azure Free Trial with $200 credit for 30 days. | 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
Azure Data Factory
Azure Data Factory has 90+ built-in connectors for integrating data from various sources. Microsoft regularly adds new connectors and update existing ones. The connectors can integrate databases, cloud platforms, big data, and SaaS applications. Popular connectors include Azure Blob Storage, Amazon S3, and Salesforce.
It also supports generic REST, OData, HTTP, and ODBC connectors. You can create custom connectors using .NET, Java, or Python. ADF provides a software development kit (SDK) for this purpose. And when you’re done with your new connector, you can share and reuse it to others in your organization. Or with other users outside your company.
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 180 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
Azure Data Factory
Azure Data Factory provides flexible and powerful options for data transformation. ADF supports various transformations, including filtering, aggregating, joining, sorting, and more.
You can use the graphical user interface to add transformations or code to create advanced data transformations. ADF allows coding in several programming languages, including SQL, .NET, Python, and others.
It also supports external activities for executing your transformations on compute services. This includes HDInsight Hadoop, Spark, Data Lake Analytics, and Machine Learning. This gives you the flexibility to use different approaches in data transformation.
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
Azure Data Factory
Azure Data Factory offers several levels of customer support. It includes free and paid options. The free support includes online documentation, community support, and email support.
Paid support options include Standard, Professional Direct, and Premier. Each has various levels of 24/7 support and faster response times. The Standard and Professional Direct support levels also come with an SLA. It guarantees a certain level of uptime and issue resolution time. Customers can reach the support team through various channels. This includes email, phone, and online chat. For premium support, customers can avail themselves of dedicated support teams and other benefits.
Azure SLA guarantees 99.9% uptime for paid Azure services.
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, Skyvia offers a prioritized support including additional support options for Enterprise customers.
Pricing
Azure Data Factory
Azure Data Factory provides a flexible pay-as-you-go pricing model. It charges based on pipeline orchestration, data movement, and data volume. Pricing can vary depending on region and usage patterns.
New customers get $200 free credit for 30 days to use any Azure service, including Data Factory. Pay-as-you-go is your next option once the trial ends or the free credits becomes zero. But ADF is always free for 5 low-frequency activities.
Some services may need resources not covered in Always Free services like storage. So, it’s crucial to check pricing and usage limits.
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.