Data integration entails channeling enterprise data from various sources into one place. Its goal is to provide a harmonized view of trusted data for querying and in-depth analytics. Below we've compiled a list of best data integration tools:
1. Centerprise Data Integrator
Astera's Centerprise automates and speeds up data integration, cleansing, and transformation. It provides a built-in job scheduler for sequencing integration and transformation workflows. You can run jobs in parallel on the platform to speed up time to value. That's possible with the cluster-based design and parallel processing engine. These help to optimize performance, including when processing massive chunks of data.
The platform has a host of built-in connectors. They work for both structured and unstructured data sources. Also, Centerprise supports data profiling and validation and code-free mapping. The data integrator includes a vast collection of prebuilt transformations.
2. IBM InfoSphere
InfoSphere is a data integration tool for extracting and transforming different data types. Its scalable runtime environment powers on-demand data integration across various sources and targets. The platform utilizes native API connectivity and parallelism. This way, it enables connection to DBMS, ERP software, and big data sources. Its streamlined interface allows non-technical users to provision data on demand. InfoSphere supports several data delivery options. These include bulk ETL, data replication, and data federation. Supported data quality functions include data profiling, standardization, enrichment, and matching.
3. Microsoft SQL Server Integration Services (SSIS)
Microsoft's SSIS is an SQL Server-based resource for managing data integration and transformations. You may use it to extract and transform data from different sources, such as relational databases and XML files. You can then load the data into a single or several data stores. It provides a simple graphical data integration interface. Thus, non-technical users can use it to develop solutions without writing programming codes. Also, SSIS has a rich set of built-in workflows. These automate and streamline data transformation and integration.
4. Informatica PowerCenter
Informatica provides a range of powerful data integration tools. It's suitable for multi-cloud, hybrid, or on-premise deployment. The resource supports many superfast connectivity options too. It has connectors for databases and data warehouses, enterprise applications, and Hadoop. It can also integrate with messaging apps and midrange systems.
With Informatica, you can ingest different data formats for transformation. Examples include XML, COBOL copybooks, and SWIFT. The tool also facilitates automatic intercompany exchange. This secure connectivity lets business partners share and collaborate on mission-critical data. Businesses can leverage Informatica's AI-driven data discovery to maximize data value, enterprise-wide.
Talend offers a graphical interface for setting up and administering integrations without coding. The tool supports many connectivity options for cloud and on-premise data sources. It has connectors for social media and apps such as Salesforce, Box, and Marketo. Thus, you may leverage its cloud API services for both app and data integration.
Talend provides a collaborative cloud-based application for data quality control. It enables teams to collaborate on data curation tasks. The software has big data integration capabilities too. These allow you to ingest and manage large datasets with Spark and machine learning.
Xplenty is another powerful, cloud-based data integration software. The tool has connectors for diverse data sources and SaaS applications. It also provides an intuitive graphical interface. The UI makes light work of building data pipelines and running ETL/ELT processes. The cloud-based platform is elastic and scalable, and it automates vital workflows. With automated monitoring, security, and scheduling, analysts can focus on the data. Moreover, Xplenty provides many resources to streamline app development. For example, developers can use API services to enhance customization. Likewise, there are connectors to ease integration with apps, such as monitoring systems.
7. Oracle Data Integration Platform (DIP)
Oracle DIP is a cloud-based data integration solution that supports data governance processes. With the open platform, you can integrate data from within Oracle and hundreds of non-Oracle sources. It uses machine learning-driven automation to meet your data integration requirements faster. The tool is ideal for real-time data replication, profiling, enriching, and transformation. Oracle DIP has an intuitive visual interface. The UI simplifies data integration tasks, enabling business users to extract value much faster.
8. SAP Data Services
With SAP Data Services, you can integrate structured and unstructured data sources. The tool enables integrations with SAP and non-SAP data stores. It also supports enterprise applications connectivity (in the cloud or on-premise). It's compatible with data warehousing platforms such as IBM Db2 and Microsoft Azure.
You may use the resource to extract and analyze unstructured documents. For this purpose, SAP supports 220 different file and text formats. The integrator can also process semi-structured data across 31 languages for analytics. It powers data curation with prebuilt address and data cleaning modules. Also, it employs parallel processing and grid computing. These capabilities help to drive high-volume data profiling and transformations.
You can stream all your enterprise data into one cloud-based location with HVR. The solution supports intra-cloud, inter-cloud, and cloud-on-premise integration. It's also possible to load your data into several targets from a single source. Integrations are possible with data sources like AWS, Azure, Db2, and Salesforce.
By using log-based change data capture (CDC), HVR enhances real-time data replication. And the use of proprietary compression optimizes storage space. Additionally, the tool is versatile and scalable. That's because it incorporates a distributed architecture and various topologies.
Hitachi Pentaho powers the efficient integration of data from diverse heterogeneous sources. Thanks to metadata injection, the platform speeds up the onboarding of complex datasets. It also provides many prebuilt, reusable templates. These help to streamline and speed up data retrieval, preparation, and blending. Pentaho's multithreaded engine scales to match growing data integration needs.
The platform offers the option to use in-cluster execution along with data-processing engines. Combining these resources increases capacity for collaboration, maximizing data productivity. Pentaho also supports big data integrations. Compatible sources include Spark, NoSQL data warehouses, and Hadoop distributions.
11. InterSystems Ensemble
Ensemble is a cloud-based solution that facilitates data and application integration. It has an extensive adapter library to deliver out-of-the-box connectivity. Thus, it enables you to access and process different file formats from standard and non-standard data sources. Supported technologies/protocols include Email, FTP, SAP, SQL, and HTTP.
What if you needed to build a custom adapter on the platform? Object inheritance and SOAP services would enable you to do that. Ensemble supports healthcare, business, and government data integration applications.
12. Information Builders
Information Builders provides a suite of data integration services. These are ideal for both conventional and non-conventional data sources. It also serves big data consolidation purposes. So you can use it to retrieve data from mobile apps, social media, and IoT devices. One of its outstanding features is B2B integration. The service enables business partners to share and track transactional data.
The cloud-based solution supports automated ETL processes. These simplify the creation and expansion of data warehouses or even data marts. Information Builders offers a broad array of off-the-shelf adapters too. The tools enable users to access and extract value from different data formats.
13. SAS Integration Studio
SAS Data Integration Studio has the features required to streamline data consolidation. One of its key features is a shared metadata environment. This architecture enhances the consistency of data standardization across all data sources. The software delivers connectivity for different data formats and platforms too. These include messaging apps, ERP, RDBMS, XML, and flat files. Other business-critical capabilities are ETL and data cleansing, enrichment, migration, and synchronization.
SAS Data Integration Studio supports data federation. The feature enables you to access and process data without moving it. Its intuitive graphical interface with repeatable workflows facilitates collaboration on data integration management.
14. Dell Boomi
Boomi is a scalable data integration solution. It can integrate on-premise and cloud apps, data stores, and IoT devices to provide a unified view of data. It has a host of connectors for diverse data sources. Supported platforms include Google Cloud, Amazon S3, NetSuite, and Microsoft Azure SQL Server.
The software helps with data mapping tools and various integration patterns. And a drag-and-drop UI simplifies workflows, even for non-technical users. Besides, Boomi includes prebuilt templates and process libraries. These features speed up the delivery of data integration projects.
Syncsort offers a comprehensive data integration suite for enterprises of all sizes. It comes with a set of big data connectors. These let you integrate various platforms to power advanced AI analytics. The software supports change data capture, database replication, and ETL processes. Thus, it has the right tools for data governance and data quality control.
With Syncsort, you can ingest IBM mainframe's operational machine data into Splunk. This integration gives you a full view of your IT environment.
16. Actian DataConnect
DataConnect provides hundreds of connectors for integrating on-premise and cloud data sources. The data integration tool lets you create reusable templates with the IDE framework. This way, you can scale by executing similar integrations superfast.
DataConnect features an intuitive graphical interface. With the UI, you need no scripting skills to develop job schedules or integration maps. Also, DataConnect incorporates REST Invoker 3.0. The easy-to-use resource simplifies the creation of web services with RESTful APIs.
17. Software AG WebMethods OneData
WebMethods OneData enhances data integration by delivering quality data from various sources. It lets you curate and validate your data. Doing this eliminates errors and redundancies across data sources, software systems, and processes. The platform supports multi-domain data modeling. Thus, it powers enterprise-driven integrations between customers, products, geospatial information, and reference data.
WebMethods OneData includes a metadata registry. So, it enhances standardization and the reusability of data components across business units. Additionally, it provides hierarchy management tools. Examples are versioning tools and a configurable business rules engine.
Data integration is essential to developing a unified, trusted data warehouse. Are you looking for a cloud-based tool to integrate all your enterprise data? Try out Xplenty today!