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Informatica's Intelligent Data Management Cloud not new tech, but covers hyperscalers' weakness in data integration
Picking up the slack on AWS, Azure, and GCP
Vendors should only be allowed to go "cloud-native" once, no matter how many times they try to pull off the publicity trick. We can decide later how we'll police this house rule – electrical clamps to the nodes, anyone? – but for now let's look a recent suspect: Informatica.
At its annual shindig this week, held online like 2020's affair because of COVID-19, the 28-year-old data integration vendor launched its Intelligent Data Management Cloud (IDMC). The accompanying guff says it is "micro-services based and API-driven" and able to scale with "elastic and serverless processing."
"The IDMC takes cloud-native to the next level, offering all services in a single cloud-native platform for data integration, app and API integration and data management," it said.
In his blog, CEO Amit Walia called it "the industry's first and most comprehensive, cloud-native, AI-powered, end-to-end data management platform."
But not all of these capabilities are new, not even to Informatica.
The company launched its CLAIRE data automation technology back in 2017, promising an Intelligent Data Platform that would "bridge existing on-premise environments with new cloud environments using familiar data integration interfaces, tools, skills and re-usable code."
In spring of last year, it launched a slew of new features. These included Cloud Data Integration (CDI) & Cloud Data Integration Elastic (CDI-E) which would offer "more dynamic, scalable, flexible data integration" improving pushdown in AWS and enhanced Azure support. It also previewed serverless runtime for CDI and CDI-E.
Meanwhile, last year also saw the launch of iPaaS for multi-cloud, hybrid environments with "more automation and intelligence."
Of note in the new announcement are low-code features in its cloud data integration suite. These are designed to promote "agility and collaboration with a low-code or no-code experience allowing customers to go directly from idea to implementation" and so on.
Although aspects of data integration across the cloud, using APIs and microservices, was not new, speaking to The Register, chief product officer Jitesh Ghai said it was the metadata, and mapping of it, held in Informatica's cloud that was novel.
"Our commitment as an independent and neutral provider is to catalogue that data, scan profile derived enriched metadata, apply AI and ML to organize that data," he said.
Such a cloud service – housing 11 petabytes of metadata, according to Informatica – was necessary to overcome the "fragmentation problem" of data in several cloud providers, as well as in disparate on-prem systems. "We're cataloguing that data wherever it exists… from metadata that might exist in applications on-premises from your legacy estate, from your Hadoop estate, from Databricks or a Snowflake or BigQuery," Ghai said.
Meanwhile, Informatica's Metadata Knowledge Graph, which exists in earlier product iterations, would help users navigate this labyrinth of enterprise metadata in its cloud.
While Informatica has its own metadata cloud – with pods hosted by each of AWS, Azure, and GCP – it also offers differing sets of enhancements to data management on those platforms. With AWS they talk about data cataloguing, quality, and governance. On Azure, there is an emphasis on "data integration and data loading." On GCP, Informatica's Cloud Data Integration Elastic (CDI-E) is focused on mass ingestion of data.
Although these features would be available on all clouds in due course, the current distinction makes senses because there are gaps in each of the cloud providers' products, plus there are specific workloads that are more prominent in one cloud over the other, said Noel Yuhanna, veep and principal analyst at Forrester Research.
He added that the new nomenclature of Intelligent Data Management Cloud (IDMC) has similarities to Informatica's earlier offer, but was more focused on the developer community and would help support integration based on access to trusted data using APIs for microservices-based custom cloud applications.
"Also, IDMC supports a broader set of business use cases, offers similar data interactions across multi-clouds, and leverages cloud-native capabilities to improve security, performance, and scale," he said.
IDC research director Stewart Bond said Informatica was adding enhancement where each cloud provider was weak in its own data integration technology.
"An Informatica service that runs and looks the same across all clouds is a great alternative compared to working with and supporting a different solution on each cloud," he said. "For example, if an organisation was doing data integration on all three clouds, they would need to work with Data Fusion (GCP), DataFactory (Azure) and Glue (AWS). Each very different in their implementation, configuration and development requirements."
But while the shift to the Informatica cloud could offer speed and flexibility, users would need to keep an eye on costs.
"Consumption-based pricing is great because you only pay for what you need, but elasticity can quickly drive costs up if workloads are not planned carefully," Bond said. ®