Best Data Integration Software
360Quadrants recognizes the below-listed companies as the best data integration software -
1. Informatica Corporation
2. IBM Corporation
3. Microsoft Corporation
4. Oracle Corporation
6. SAP SE
7. Information Builders Inc
9. SAS Institute Inc
10. Boomi Inc
Data Integration Software Overview
The overall data integration software market is expected to grow from USD 6.44 billion in 2017 to USD 12.24 billion by 2022, at a CAGR of 13.7%.
Market growth is attributed to the demand for tools combining several heterogeneous data sources and the rise of cloud computing, creating demand for effective data integration tools and services. There has been a massive amount of data generated from multiple systems in various organizations. Data integration has provided relevant solutions to look into this data, as consolidated information in a consistent manner.
Data integration enables companies to look into the data holistically and improves their decision-making capabilities. Data integration becomes absolutely necessary in case of mergers and acquisitions, where the top management needs to be aware of all the pertinent data to take necessary actions and to attain desired results.
26 companies offering top data integration software were analyzed, shortlisted and categorized on a quadrant under Visionary Leaders, Innovators, Dynamic Differentiators, and Emerging Companies to identified best data integration software providers.
The competitive leadership mapping (Quadrant) showcased below provides information for 20 top data integration software. Vendor evaluations are based on two broad categories: product offering and business strategy. Each category carries various criteria, based on which vendors have been evaluated. The evaluation criteria considered under product offerings include the breadth of offering, delivery (based on industries that the vendors cater to, deployment models, and subscriptions), features/functionality, delivery, product quality and reliability, and product differentiation. The evaluation criteria considered under business strategy include geographic footprint (on the basis of geographic presence), channel strategy and fit, vision alignment, and effectiveness of growth (on the basis of innovations, partnerships, collaborations, and acquisitions).
Vendors who fall into this category receive high scores for most of the evaluation criteria. They have strong and established product portfolios and a very strong market presence. They provide mature and reputable data integration tools. They also have strong business strategies.
They are established vendors with very strong business strategies. However, increasing their product portfolios will take them to new levels. They focus on a specific type of technology related to the product.
Innovators are vendors that have demonstrated substantial product innovations as compared to their competitors. They have very focused product portfolios. They need to develop their growth strategy for their overall businesses.
They are vendors with niche product offerings, who are starting to gain their position in the data integration market. They do not have very strong business strategies as compared to other established vendors. They might be new entrants in the market and require some more time before gaining significant market traction.
Data Integration Software Market Segmentation
The data integration software market is segmented into tools and services -
Tools - As the volume of data generated and collected by enterprises increases, the need for integrating the data from numerous disparate sources also grows rapidly. The proliferation of data amounting to ‘big data’ has forced companies to develop and design data integration software to help teams simplify and manage processes. With myriads of data integration tools in the market, organizations need to understand their data requirement and then deploy the software.
Enterprises deploying the data integration tools look for cost-effective, scalable solutions that would help them to integrate their data sets and gain a unified and consistent view of the enterprise-wide data. The main technologies for data integration are ETL, EAI, EII, which is also known as data virtualization.
Services - The data integration segment constitutes professional services and managed services. The services are an integral step in the deployment of solutions that can be catered by the solution and service providers or can be outsourced to third-party vendors. Services constitute an essential part of the software life cycle, which includes product up-gradation, maintenance, training, consulting, and others.
In the age of the digital economy, enterprises are evolving and demanding new ways to improve their Return on Investments (RoI) and business optimization. To boost growth and generate higher revenue, enterprises are turning toward services that are instrumental in streamlining business operations and optimizing business resources. Managed services play a crucial part in reducing overheads of the enterprises, facilitating them to be product-focused and innovation-friendly. Thus, services play a pivotal role in transforming new-age enterprises, which are laid on the pillars of Volatility, Uncertainty, Complexity, and Ambiguity (VUCA) in today’s dynamic world. The services segment in the data integration market is expected to witness the highest growth rate in the coming years, which is evident from the proliferating product adoption in the present year.
- Managed Services - Managed services are viewed as significant, as they are specifically related to client experience; enterprises cannot bargain on this variable, as it helps them to maintain their market position. Moreover, it has become difficult for companies to focus on core business processes and support various other functions, which in turn increases the significance of managed services. These services offer technical skills that are required to maintain and update software in the data integration ecosystem. All the pre- and post-deployment questions and needs of clients are taken care of under the managed services unit. Organizations mostly outsource such services to offer clients on-time delivery.
- Professional Services - Professional services are categorized into three types, namely, system deployment and integration; training, support, and maintenance; and consulting services. Professional services are delivered to the customers after the purchase of a product. The services are an integral part of deploying the solutions in an organization, imparting training, handling and maintaining the use of the software. Professional services include designing, planning, upgrading, and hosting consulting services imparted to the clients. Companies offering these services encompass consultants and dedicated project management teams that specialize in the design and delivery of critical decisions, support software, tools, services, and expertise. The growth of the professional services segment is mainly governed by the complexity of operations and the growing deployment of data integration systems in the organizations. Companies such as IBM Corporation, Cisco Systems, Talend, and Informatica offer unmatched services to the customers to smoothly run their systems and achieve maximum security and operational efficiencies.
Why should you use Data Integration Software?
Data Importance – Organizations generate more data then revenue daily. Successful organizations recognize the importance of this data and convert them into actionable insights. Data generated by organizations comes in though different sources and each of those datasets have nuggets of critical information that can be used to promote and grow businesses. Data Integration Software allows an organization to view and use the information in a manner that can facilitate growth for the business.
Software Compatibility – Data Integration Software enables data from across various sources to be stored and compiled in one location or in structured formats. This helps users to access the data easily for any third-party software such as data visualization tools to generate specific updates, charts, insights, etc.
Data Complexity – Data in organizations is generated by various departments such as sales, marketing, research, finance in different formats for different purposes. Mostly, the data is not in the same structure and it proves complex for departments to understand or use each other’s data. Data Integration Software allows the data to be stored in one place and in structure, formats making it easier for employees across the organization to access and understand the data.
Data Value - Bringing disparate datasets together increases the value of the information. With a good data integration software users can play around and compile data from various sources bring out more value in the overall data or output.
Accessibility and Collaboration – With data integration software data is more accessible to all users from an organization. This makes collaborating with various departments easy and more efficient.
How does Data Integration Software work?
Database - Data Integration Software works on the premise of a database. A database is a collection of data stored in a particular format or structure. However, this data is stored in a raw form. The data needs to be classified for further use.
Data Classification – Data from the database is classified depending on either the type of data or on how the data is organized in the database. An organization of data in the database is known as a schema. E.g. – The data can be classified in tables or in number format for numerical values or in a media format for videos.
The most commonly used classification is the Object-Oriented Programming (OOP) which focuses instead on defining data as objects and then determining how different objects relate and interact with one another.
Information Access – Once the classification is done, to access the data a user needs to type or input a query. A query is basically telling the software what you want to view. Queries rely on special computer languages such as Structured Query Language (SQL). Once a query is inputted the database responds to the query by sending data that meets the requested parameters.
Top Data Integration Software Features
Some of the top features of a data integration software are –
Quick Decisions– A data integration software stores data in various formats all in one location. This allows users to view and utilize data from multiple departments simultaneously and quickly. Stakeholders can take timely and effective decisions in an efficient manner.
Multiple Sources – Organizations have various departments and data is generated by each of those departments. Data Integration enables users to view information from multiple sources from one central location.
Growth and Operations Improvement – As the data is integrated with the help of a data integration software trends, interlinking and cross-connection in data can be observed. This gives stakeholders a bird’s eye view of the entire process or operations. Improvements can be made to ongoing process and strategies can be identified for growth. Operations can also be streamlined.
Real-Time Data – Top Data Integration Software can provide data in real-time making the decision-making process and monitoring much easier. Information that would take a long time to create, sometimes even months is available quickly.
Use CasesSome of the areas where data integration can be used are –
- Data Migration
- Data Syncing
- Dashboard Creation
Best Data Integration Software in 2022
Scribe ready-to-go connectors adapt to software updates, it is a simple graphical interface for code-free customization and management tools that keep things working smoothly. Scribe, works with connecting data among apps that our business groups are always asking for new data integrations which in turn helps in driving business efficiency. Scribe’s Agile Integration Platforms helps for large Enterprises, Small to Medium Businesses, Systems Integrators, and SaaS Providers. Sribe offers a lot of flexibility and configurability so one can connect data from one system to just about any other system we need to. Scribe also offers connectors to many other enterprise applications, so one has the option to streamline data movement to other systems in the future.
Elasticio hybrid integration platform has a rich library of pre-built connectors for mainstream business applications. Elasticio helps in transforming data between various applications and systems by mapping data into specific fields where the next generation components expect to receive.It helps in detecting inconsistencies in integration workflows to find the source of errors and fix rebelling workflows within short span of time. The company’s hybrid integration platform is easily connected to existing on premise or deployed on premise. The benefit of using Elasticio is that the platform is easily extensible which ensures fast development of new integration components with minimum efforts. elasticcio provides developers with a complete integrated suite of tools and technology that make connecting disparate software easier, less time-consuming and more cost-effective.
Jitterbit delivers powerful, flexible, & easy to use data and application integration solutions. Jitterbit allows companies of all sizes to integrate any On-Premise, Cloud , Social, or Mobile application. Jitterbit's graphical "No-Coding" approach accelerates and simplifies the configuration and management of complex integration projects. Jitterbit helps in removing the complexity from data integration with visual interface and wizard-driven tools. The company is effectively capturing, managing and leveraging raw data to derive meaningful business intelligence (BI) for enterprises. The company builds data integration and ETL processes, with business experts deploying the data integration technology. Jitterbit’s powerful ETL tools and data integration solutions provide an intuitive, easy-to-use interface that simplifies data integration.
Pentaho Multithreaded data integration engine scales up and out and includes deployment to clustered and cloud environments. The company’s dynamic and reusable data integration templates enables users to create transformations on the platform. It manages and processes data in on-premises, hybrid and multicloud environments. It effortlessly switches from data-processing engines with in-cluster execution to increase data productivity. It also helps reducing the time needed to provide data models for business users, improving collaboration between business and IT. It helps in reducing development time by using data services to virtualize transformed data and making the data available for reports and applications.
The company uses Relational Database integration which is possible using intelligent and patented AppComms. The simple drag and drop interface of Enterprise Enabler provides users with a relational view of existing relational and non-relational databases on any imaginable platform. Stone Bond’s Relational Database AppComms offers the broadest range of integration options which enables users to access to data in operational systems, federate and sync data in warehouses without staging or designing architecture to address the unique information needs of all users.
The CloverDX previously known as Cloveretl, differentiates itself from competitors, based on the quality of its products in harmony with outstanding levels of service. The company goes extra mile to make things happen and respond rapidly to requests, never taking its customers for granted. It provides a full set of database readers and writers, JSON, XML and CSV processors, complex field mapping, email parsing, data aggregation, sorting, de-duplication and many other integration components. The technical support and maintenance package offered includes direct access to a dedicated customer portal and support team, who are right next to their developers and data consultants.
Bedrock integration starts with selecting from wide range of connectors including HubSpot, Marketo, Pardot, ConnectWise, Salesforce, Microsoft Dynamics, NetSuite, SugarCRM, Zoho CRM, Pipedrive, Infusionsoft, Cvent and more. It can connect more than two systems at a time and map specific fields including custom fields. It provides the option to leverage object relationships e.g. to pull data from an account to a contact record, which opens data flexibility. It also pairs the data across the system by using uniques identifier for each object type. As new data comes into any connected system, it gets paired using the unique identifier. Unlike native connectors that tend to sync in only one direction, this de-duplication and pairing process works in all directions, keeping data de-duplicated & clean.
Acxiom is a technology and services company that offers the data foundation for the world's best marketers. They permit people based marketing everywhere through a simple, open approach to connecting systems and data that drives seamless customer experiences and higher ROI. They assess omnichannel data sources, formats and systems to ensure the best Open Garden architecture. Their architect solutions for tech stack enables data orchestration that is focused on a specific strategy, budget, and challenges to achieve optimal sustainability and ROI. They help in configuring data environments for true omnichannel identity resolution and activation across apps and platforms. They connect new and existing applications with data environments for efficient data orchestration. They help in optimizing capabilities and performance and enables growth in new data sources, channels and use cases.
Wipro’s IP NextGen DI solution shifts the creation of data integration components from individual job-based to pattern based. It offers rich user interfaces and an extensible pattern library to reduce development effort drastically and delivers high-quality ETL code consistently. It offers Pre-built pattern libraries to help kick-start big data, digital and traditional data integration projects. While responding to current data integration needs beyond ETL development, the IP tool also provides other critical modules such as Pattern Discovery for design identification of existing ETL, Batch Analysis on data flow dependencies for batch optimization and source-to-target Data Lineage document generation.