Increase productivity, optimize costs, and democratize data across your multi-cloud environment with cloud ETL and ELT. Integrate data sources at scale and with ease. Cloud Data Integration covers diverse sets of patterns, use cases, and users, ensuring you have well-architected and seamlessly automated data pipelines.
Build and run advanced, complex integrations and achieve elastic scale with Spark processing, in a serverless environment.
Use a flexible and cost-effective option, whether ELT pushdown, ETL, or Spark
Drag and drop 100+ prebuilt functions, transformations, and templates for building data pipelines.
Easily scale up or down and only pay for what you use from our industry-leading cloud services.
Ingest data with high-performance ETL, mass ingestion, or change data capture.
Integrate data on any cloud, with ETL, ELT, Spark, or with a fully managed serverless option.
Integrate any application, whether it’s on-premises or SaaS.
Process petabytes of data up to 72x faster within your cloud ecosystem.
See how you can use Informatica’s Cloud Data Integration to quickly start building high-performance data pipelines to meet any data integration need.
Informatica Is a Leader Again in 2021 Gartner® Magic Quadrant™ for Data Integration Tools
“We found that Informatica Cloud Data Integration was the most flexible data integration solution and would be the easiest for business users to adopt. We started using it for the simple use case of backing up new Salesforce leads to our marketing database, and it quickly became the backbone of our marketing data ecosystem.”
David Latka
Cloud Mass Ingestion
Efficiently ingest databases, files, and streaming data for real-time data replication and streaming analytics.
Cloud Application Integration
Integrate apps and data in real time with intelligent business processes that span cloud and on-premises sources.
Cloud Data Quality
Quickly identify, fix and monitor data quality problems in cloud and on-premises business apps.
Advanced Serverless Cloud Data Integration
Focus on building data pipelines and applications without worrying about managing infrastructure.
