Data integration is the process of combining unstructured data from heterogeneous and disparate sources to get a unified view. Extract, transform, load (ETL) is an important step in data integration, where the data is copied from multiple sources into a destination system. The process involves extracting the data from different source systems, then transforming the data (like formatting data, applying calculations and concatenations) and finally loading the data into the data warehouse.
The right data integration tool helps to accelerate data processing, find new ways to connect and use data, and cut down costs and time related to manual data management processes. Here are some of the top data integration platforms in terms of market share, along with a look at their platform and how it fits into the overall data integration marketplace.
ETL with Amazon Web Services (AWS)
AWS is a CSP that focuses more on data integrity and security. AWS offers a set of products to perform both legacy ETL data integration and cloud ETL data integration. They include the below products:
|AWS Import/Export Snowball
|Useful for petabyte-scale data transport
|A managed ETL service
|AWS Database Migration Service
|Used to move entire databases
|AWS Data Pipeline
|Used to transport data from on-premises systems to AWS computing environments
AWS provides robust data management consoles and strong analytics capabilities. The platform includes Amazon S3 (Simple Storage Service), Amazon Redshift, and Amazon VPC (Virtual Private Cloud). It supports Informatica, Alteryx, and Matillion. Besides, AWS supports ELT architecture, pushing the transformation part straight into the database.
ETL with Informatica
Informatica is one of the leading data integration platforms. The tool supports major types of data migration and transformation. It supports platforms such as AWS and Azure. The platform guarantees a high level of automation and performs data validation across development, testing and production environments.
Informatica supports on-premises, multi-cloud, and hybrid data integration in real time and batch processing modes. Moreover, Informatica uses native connectors to support major data formats and data structures. This includes industry specific formats such as EDI X12, HL7, and SWIFT.
Informatica offers distributed processing, adaptive load balancing, dynamic partitioning, high availability, grid computing, and pushdown optimization. Consequently, the platform ensures a highly scalable and stable environment.
Pentaho Data Integration (PDI) operates in a no-code environment supported by visual drag-and-drop tools. Besides, the platform supports real-time data ingestion, data cleansing, data blending, and data preparation. PDI works with major data types and data formats. The tool includes a powerful metadata injection option to manage enterprise data. Also, it includes orchestration capabilities to assist in coordinating data and combining data.
Pentaho approaches big data integration with a zero-coding strategy. Also, the platform allows users to switch between different analytics execution engines. The tool supports Spark, Hadoop, and NoSQL objects. It connects to different business applications such as Google Analytics and Salesforce.
PDI checks data under process, which accelerates the data validation process. The tool contains powerful orchestration capabilities. Also, the platform includes an enterprise scheduler to coordinate workflows. In addition, the tool ingests nearly any open-source database, relational database, and file format.
ETL with Skyvia
Skyvia is a SaaS data platform following a wizard-based and a no-code data integration approach. Users with no knowledge of ETL and data integration can use this tool. The GUI includes asset of templates and editors to pull data into the cloud and manipulate the data. Furthermore, the platform facilitates strong mapping features and powerful automation features for bi-directional synchronization of data. The bi-directional sync feature ensures real-time data availability.
Skyvia generates reports and dashboards supporting multiple formats such as CSV, FTP, SFTP, SQL, Azure SQL, Amazon S3, Amazon RDS, G Suite, Oracle, Magento, Dropbox, Stripe, Dynamics 365, and Salesforce, to name a few. Also, the platform includes the ability to export the linked object data and strong data export features.
ETL with Fivetran
Fivetran is a new-gen data integration platform, focusing on full data replication in a no-code and zero-maintenance framework. It offers automated data connectors suitable for major database formats. Furthermore, the platform helps to get the complete view of an organization by connecting multiple data sources to a central data warehouse.
Fivetran’s centralized data warehouse concept simplifies data management, promotes automation, and enables enterprises to focus on BI and analytics. The platforms hosts an extensive set of connectors for major applications and protocols. Supported applications and protocols include Oracle, Salesforce, Zendesk, GitHub, Marketo, HubSpot, Stripe, Shopify, Zero, Mailchimp, Workday and FTP.
Microsoft is a legacy data integration platform, supporting data residing in both cloud and SQL database server. Azure Data Factory (ADF) is a hybrid data integration service based on a no-code environment. The tool helps to extract data from heterogeneous data sources and transform them in cloud repositories. Moreover, ADF offers robust data mapping features to connect the data to different analytics platforms.
SQL Server Integrated Services (SSIS) provides strong data transformation capabilities through a drag-and-drop interface. Users can integrate data from different tools and applications, including Salesforce.
ADF helps to extract data from heterogeneous data sources, including SSIS. The tool consists of connectors supporting more than 80 external data sources (including Apache Cassandra, AWS, IBM Db2, and different Azure repositories). ADF accommodates both on-premises data and cloud data. The platform supports both custom codes and codeless UI.
SSIS simplifies data movement using import/export wizards. Also, the tool includes built-in scripting and a catalog database to store, execute and manage packages. Besides, SSIS completely automates SQL database server’s maintenance.
Oracle Data Integrator (ODI) offers a GUI-based cloud data integration. ODI supports a declarative programming style. The platform is designed for larger corporations with major data migration and data management requirements.
ODI supports major databases such as IBM Db2, Netezza, Teradata, Exadata, Sybase, Hadoop. ODI leverages the current RDBMS capabilities to integrate with other Oracle products for processing and transforming data. The platform intends to reduce hand coding using robust mapping features and automation features.
SAP Data Services
SAP Data Services is a platform for large-scale data migration and ETL-based data integration. It is suitable for moving large volumes of data between on-premises legacy systems and the cloud. Moreover, the platform offers a GUI, robust connectors, and tools to support versatile ETL scalability. As a result, the tool achieves impressive flexibility through prebuilt data models, transformation logic, and data flows.
SAP Data Services is tightly integrated with SAPs Rapid Marts. Consequently, the platform leverage ETL options which are optimized for end-user query, reporting, and analysis. The tool can extract data from different systems, including Siebel, SAP R/3, Oracle J.D. Edwards, and PeopleSoft. Also, it provides features to build, test, and manage ETL jobs.
SAS Data Integration Studio (DIS) supports data from multiple heterogeneous sources and different operational systems. The platform modifies, restructures, and consolidates data as required. Besides, the tool provides real-time data integration as the data is being replicated, moved, or synchronized.
Data Integration Studio allows users to query data and use them across multiple platforms. Moreover, the platform facilitates virtual access to legacy files, text files, database structures, XML sources, message queues, and ERP applications. This enables users to integrate data across virtual data sources and empower real-time analysis.
Talend provides two ETL-based data integration products: Talend Data Integration and Stitch. These products are known for speed, flexibility, performance, scalability, and ease of use. Their focus lies on moving, transforming, and synchronizing data from heterogeneous sources. The platform supports cloud platforms such as Azure, AWS, and Google. Besides, the tool supports enterprise apps such as Dropbox and Salesforce. Also, it supports integration platforms based on ETL, ELT, real-time processing, and batch processing.
Talend includes team collaboration features, visual mapping, CI/CD (Continuous Integration and Continuous Delivery), data governance and security options, including fraud pattern detection.
Xplenty is a cloud data platform used to integrate data from different repositories, applications, and other sources. This SaaS ETL platform supports Amazon Redshift, Azure Synapse, Google BigQuery. Moreover, Xplenty is a highly scalable, flexible, and secure data integration platform that provides a wide range of APIs.
Xplenty utilizes built-in connectors to integrate with more than 100 data stores and applications, including AWS, Google Cloud, Microsoft Azure, Salesforce, Magento, Facebook, and Slack. The tool uses a package designer to execute a wide range of data integration use cases. The GUI promotes a no-code environment, and the tool runs the packages from an API or directly from the user interface. Consequently, the platform simplifies job scheduling, job monitoring, and managing status reports and other orchestration information.