Big Data Management
Enable faster, flexible, and repeatable big data ingestion and integration.
Overview
Intelligently manage big data on-premises and in the cloud for faster insights.
Accelerate productivity
Accelerate data engineering productivity with a visual design interface that features parameterized development and ensures the adoption of the best open source innovations.
Accelerate performance
Execute data processes for highest performance, scalability, and utilization without any knowledge of the underlying specialized data platform technologies.
Accelerate data integration
Simplify and accelerate big data integration with mass ingestion and connectors to hundreds of data sources such as databases, apps, or the cloud.
Accelerate the move to cloud
Automate the deployment and management of distributed resources with a serverless architecture.
Key Features
The industry’s most advanced big data management product that accesses, integrates, cleans, catalogs, and governs big data.
Universal Data Access
Access all types of data including transactions, applications, databases, log files, social, machine, and sensor data.
Advanced Spark Support
Leverage innovations in the latest Spark engine for advanced data management capabilities, including data ingestion, data quality, data masking, and stream processing.
Data Integration on Hadoop and Spark
Access an extensive library of advanced prebuilt data transformations, including Python transformations to operationalize data science projects.
Visual Design Interface
Builds on top of the open-source Hadoop framework and preserves all the transformation logic without specialized development.
High-Speed Mass Ingestion
Ingest data from source systems and applications into cloud and big data using high-performance connectivity, mass ingestion, and dynamic mappings.
Flexible Deployment
Deploy and manage big data workloads automatically both on-premises and in cloud environments, such as Amazon AWS, Microsoft Azure, and Google Cloud Platform.
Data Profiling on Hadoop
Profile data on Hadoop to understand the data, identify data quality issues, and collaborate on data pipelines.
Serverless Management
Automate deployment and management of Hadoop clusters with Spark Serverless services, such as Databricks, Qubole, and Google Dataproc.
Intelligent Data Parsing
Parse complex multi-structured, hierarchical, and unstructured data automatically with Informatica Intelligent Structure Discovery. Easily handle schema drifts.
Operational Insights for Big Data
Give data ops a single view to monitor and plan big data resources. Achieve better compliance and performance management.
Big Data Management in the Cloud
Big Data Management on AWS
Leverage the security and scalability of the managed Hadoop framework in AWS EMR to easily find, prepare, and govern big data to quickly drive business value.
Big Data Management on Microsoft Azure
Leverage the flexibility of the managed Hadoop framework in Microsoft Azure HDInsight to easily find, prepare, and govern big data to quickly drive business value.
Integration at Scale
Process big data integration tasks without managing servers or requiring big data expertise using the cloud-native Integration at Scale service.
Informatica Operational Insights
Use machine learning to efficiently monitor and manage your Big Data Management deployments across domains and locations.
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Customer Success Stories
M.D. Anderson Cancer Center
Informatica empowered scientific and clinical collaboration at this renowned cancer center by turning data into knowledge and facilitating self-service business intelligence.
Tinkoff Bank
Tinkoff Bank acquires and retains more customers at a lower cost with Informatica Big Data Management.