Top 9 ETL Tools For Data Integration In 2020
One of the essential aspects of data warehousing is the ETL (Extract Transform Load) tool. An ETL tool is a combination of three different functions in a single tool. One most crucial property of ETL is to transform the heterogeneous data into homogeneous one, which later helps data scientists to gain meaningful insights from the data. In this article, we list down the top 9 ETL tools one must use for data integration in 2020. The list of top 9 ETL tools is in alphabetical order. Apache NiFi Apache NiFi has been built to automate the flow of data between systems. It supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. It executes within a JVM on a host operating system. The primary components of NiFi on the Java Virtual Machine (JVM) are web servers, flow controllers, extensions, and content repository, among others. Some of the intuitive features include Web-based user interface: NiFi provides a seamless experience between design, control, feedback, and monitoring.Highly configurable: NiFi has low latency, and the flow can be modified at runtime. AWS Glue AWS Glue is a fully managed serverless ETL, which is simple as well as cost-effective to categorise data and to move it between various data sources. AWS Glue consists of a central metadata repository known as the AWS Glue Data Catalog, an ETL engine that automatically generates Python or Scala code, and a flexible schedule that handles dependency resolution and job monitoring. Some of the intuitive features include AWS Glue generates ETL scripts to transform, flatten, and enrich your data from source to target.It detects schema changes and adapts based on your preferences. Informatica PowerCenter Informatica PowerCenter is a metadata-driven data integration platform which helps in accelerating data integration projects to deliver data to businesses quickly. Some of the intuitive features include Scalability, performance, and zero downtime: PowerCenter provides support for grid computing, distributed processing, high availability, adaptive load balancing, dynamic partitioning, and pushdown optimisation.Real-time data for applications and analytics: PowerCenter provides accurate and timely data for operational efficiency, next-generation analytics and customer-centric applications. Infosphere Information Server By IBM IBM InfoSphere Information Server is a data integration platform which enables a user to understand, clean, monitor, transform and deliver data. The platform provides massively parallel processing (MPP) capabilities to deliver a highly scalable and flexible integration platform that handles all data volumes, big and small. Some of the intuitive features include Integrate data across multiple systems: In this platform, one can get near real-time integration of all types of data.Assess, analyse and monitor data quality: One can derive more insights from the enterprise data through integrated rules analysis on the scalable platform. Microsoft – SQL Server Integrated Services (SSIS) Microsoft SQL Server Integration Services (SSIS) is a platform for building high-performance data integration solutions, including extraction, transformation, and load (ETL) packages for data warehousing. SSIS includes graphical tools and wizards for building and debugging packages, tasks for performing workflow functions such as FTP operations, executing SQL statements and much more. Oracle Data Integrator Oracle Data Integrator is a comprehensive data integration platform which covers all data integration requirements from high-performance batch loads, trickle-feed integration processes to SOA-enabled data services. It includes interoperability with Oracle Warehouse Builder (OWB) for a quick and simple migration for OWB customers to Oracle Data Integrator, ODI12c. Some of the intuitive features include Faster and simpler development and maintenance.Data quality firewall: Oracle Data Integrator ensures that faulty data is automatically detected and recycled before insertion in the target application. Qlik Replicate The data integration platform at Qlik known as Qlik Replicate is a simple data integration tool which supports a variety of use cases including mainframe modernisation, Oracle to Hadoop migration, and real-time data warehousing. This platform automates the replication processes end-to-end, which include target schema generation across all major relational databases, data warehouses, and Hadoop distributions in the data centre or the cloud. SAS – Data Integration Studio SAS Data Integration Studio provides a powerful visual design tool for building, implementing and managing data integration processes regardless of data sources, applications, or platforms. It enables users to build and edit data integration quickly, to automatically capture and manage standardised metadata from any source, and to easily display, visualise, and understand enterprise metadata and your data integration processes. The studio is an easy-to-manage, multiple-user environment which enables collaboration on large enterprise projects with repeatable processes that can be easily shared. SAP – BusinessObjects Data Integrator SAP – BusinessObjects Data Integrator helps an organisation to extract, transform, integrate and load your data in the analytical environment. With SAP BusinessObjects Data Integrator, one can easily extract data from any source, transform, format and integrate that data into almost any target database.
One of the essential aspects of data warehousing is the ETL (Extract Transform Load) tool. An ETL tool is a combination of three different functions in a single tool. One most crucial property of ETL is to transform the heterogeneous data into homogeneous one, which later helps data scientists to gain meaningful insights from the […]
One of the essential aspects of data warehousing is the ETL (Extract Transform Load) tool. An ETL tool is a combination of three
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