Blendata Enterprise Certified

Unify all big data and advanced analytics capabilities into one platform, covering data integration, data management and security, processing and analytics, and data utilization. Simplify these features into a single interface with low-code capability, powered by best-in-class technologies such as Apache Spark and Delta Lake.

Integrate data from various sources, such as *Oracle, MySQL, Amazon S3, and others, effortlessly using built-in connectors and advanced ingestion techniques like change data capture. Store data in standardized big data formats like Apache Parquet or Lakehouse formats like Delta Table. Process and analyze the data using SparkSQL, PySpark, or a suite of bundled open-source AI/ML libraries via a SQL editor or notebook interface—all within a single Data Lakehouse platform.

Automate efficient data pipeline operations, including ingestion, SQL scripts, notebooks, and ML/AI utilization. With low-code workflow orchestration, users can easily schedule workloads without the need to write complex Python DAGs or scripts. The platform also provides a job monitoring and management console, enabling seamless oversight. This empowers organizations to execute complex operations and automation tasks with minimal effort.

Offers enterprise-grade security and governance with powerful features like user/role-based access control, data masking and hashing for PII data, Data encryption with external KMS supported, and even granular column or row-level security

Provide a familiar notebook interface for data engineers, data scientists, and ML developers, supporting popular programming languages like Python, R, Scala, and SQL with Apache Spark-based library.

With the de facto standard technology like Apache Spark as our main engine. It’s not just capable but easy to develop, integrate, or move data or workloads to other platforms with minimal efforts. Unlike other proprietary technologies that strictly locking customer data and workload within their ecosystem.