A common starting point for enterprises transitioning to big data is offloading unused data and ETL workloads from a data warehouse to big data platform. Hadoop and other platforms provide a cost-efficient way to store data and do bulk processing of large data sets. Cost is the leading driver in this use case. Many of our key clients ask us how to incorporate tools to best migrate to a big data platform?
Data migration tools built from scratch is not an efficient and cost-effective option. We suggest looking for these capabilities when selecting a software tool.
- Interoperability
- Scalability
- Security
- Speed
In addition, many companies are migrating some or all their data to the cloud to increase scalability and reduce the need for internal resources.
The following highlights some of the key strengths of various leaders who offer data integration tools.
Informatica
Informatica is known to have a strong product strategy for data management, iPaaS and big data. Informatica continues to invest in its artificial intelligence-powered engine — and its data catalog offering for metadata-driven integration. These provide clients with advanced capabilities in integration.
Informatica has the ability to share metadata across its data integration tools and its other data management solutions, and this allows customers to use Informatica across a broad range of use cases.
Informatica continues to expand its global partner network of more than 500 partners and multiple independent software vendor ecosystems. For pricing options, they require a custom enterprise quote via phone or web form.
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IBM
IBM’s has more than 10,700 customers in the data integration product set. IBM is known for its modernized integration tools and has introduced machine-learning-enabled data integration. In the past year, IBM has added flexible pricing. It has moved toward subscription and cloud-based offers and pricing. Customers can purchase credits and apply these to different components based upon current needs. IBM has a strong market presence and has utilized its customer base to develop many approaches to solving complex integration challenges.
Pricing varies by solution feature set, but is estimated at $80/user/month for Professional Enterprise.
SAP
SAP offers tons of functionality, capabilities, and complex use cases. SAP customers value their data integration tools and adjacent products. A focus on cloud and AI increases the relevance of their solutions. SAP continues to be on the forefront of business and technology trends and combines data management technologies, active metadata, HIP and various enabling components that distribute, optimize and recompose integration processing.
Pricing varies by solution feature set, but is estimated at $80/user/month for Professional Enterprise.
Talend
Talend is a smaller player but excels in the cloud and leverages open source. Talend has developed specific capabilities leveraging Docker deployment and Apache Beam, which is based on Google’s Cloud Dataflow. Talend has technology partnerships with Cloudera Navigator and Hortonworks, for their integration with Apache Atlas.
Talend’s portfolio, including data quality, MDM, and the recently added API management tooling, strengthens synergies across data management and infrastructure related use cases. Talend’s pricing remains significantly lower than any of the other leaders in the market.
Talend’s pricing model depends on the pricing plan and products selected. Annual subscriptions start at $12,000.
SAS
SAS customers are highly loyal and report high-quality engagements for services. Their tools are flexible and SAS’s proven strengths span integrating and sharing data. SAS tools rate high in usability and have enhanced capabilities including interactive interfaces and machine learning functions. In addition, SAS’s data integration tools benefit from its strong data and analytics portfolio.
SAS pricing starts at $9,000/year and requires as custom vendor quote.
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Oracle
Oracle is strong in serving business users who focus on integrating governance and data quality during data integration. Oracle has also restructured pricing more aligned with the market and offers a free trial component. Customers can purchase by volume or compute capacity and pay for credits which can be applied to various products.
Oracle also supports big data SQL, plus streaming in the cloud and on-premises, and both are supported with in-built data virtualization. Oracle can be difficult to learn, and customers will need an overall plan for implementation, as opposed to figuring it out as progress is made. In addition, the initial setup can be difficult with low ease of use.
Oracle is estimated to cost $150/named user/month with advanced database schema service at $1000/month.
Conclusion
The players listed above are leaders in the data integration tools market. This market includes tools for rationalizing, reconciling, interpreting and restructuring data between diverse approaches. They are designed to support leaders in transforming data access and delivery in the enterprise.
The data integration market is ever evolving. Smart technologies like AI, Sensors, Machine Learning, and Augmented Analytics generate overwhelming amounts of data. Enterprises are focusing on bringing value to their business through the use of this data. Organizations should ensure that the integration tools they are purchasing take into account these trends and their needs. Their software tool and vendor should help them navigate through obstacles. We recommend that our clients discuss these trends before investing in a data integration tool.