As enterprises generate massive volumes of diverse data types—from structured transactional data to unstructured logs, sensor data, and social media feeds—traditional relational databases alone cannot meet all storage and processing needs. To address this challenge, organizations increasingly rely on data lakes and NoSQL databases for scalable, flexible storage and advanced analytics.
SAP Datasphere, SAP’s cloud-native data management platform, plays a pivotal role in bridging the gap between traditional SAP systems and these modern data repositories. This article explores how SAP Datasphere integrates with data lakes and NoSQL databases, enabling seamless data unification, enhanced analytics, and a comprehensive intelligent enterprise data strategy.
Data lakes are centralized repositories that store large volumes of raw data in native formats—structured, semi-structured, or unstructured. They enable organizations to collect all types of data at any scale, typically using cloud storage services such as Amazon S3, Azure Data Lake Storage, or Google Cloud Storage.
NoSQL databases offer schema-flexible, horizontally scalable solutions optimized for specific data models:
These databases handle diverse workloads such as real-time analytics, IoT telemetry, or social network data.
Integrating SAP Datasphere with data lakes and NoSQL databases offers multiple benefits:
SAP Datasphere supports connectors and adapters to connect with popular cloud data lakes like Azure Data Lake Storage and Amazon S3, enabling ingestion or virtual access to raw data.
For NoSQL databases such as MongoDB or Cassandra, Datasphere can integrate through JDBC/ODBC connectors, REST APIs, or middleware platforms like SAP Data Intelligence to facilitate data extraction and transformation.
Using data virtualization, SAP Datasphere can create virtual tables and views over data stored in data lakes or NoSQL stores, allowing real-time querying and joining with SAP data without data duplication.
For scenarios requiring data transformation or enrichment, Datasphere can orchestrate data pipelines that extract data from lakes or NoSQL sources, transform it (using SQL or visual tools), and load it into optimized SAP-managed tables for analytics.
SAP Data Intelligence complements Datasphere by handling complex orchestration, metadata management, and machine learning pipelines across data lakes, NoSQL stores, and SAP systems—creating a unified data fabric.
Integrating SAP Datasphere with data lakes and NoSQL databases is key to building a flexible, scalable, and comprehensive data strategy in the intelligent enterprise. By bridging structured SAP data with vast, diverse external datasets, organizations can unlock deeper insights and accelerate innovation.
Leveraging SAP Datasphere’s integration capabilities—supported by data virtualization, connectors, and orchestration tools—helps businesses create a unified, governed, and business-ready data foundation across the entire data ecosystem.