Data Integration & ETL
Integrate data from various sources and process it with the power of Blendata's Big Data engine, the optimized Apache Spark. Shorten processing times by at least 2x compared to traditional ETL tools.
THE SOLUTION
Leverage the Big Data processing engine for your reporting and BI workloads, instead of relying on traditional ETL tools.
Faster
Speed up your processes by at least 2x compared to traditional ETL tools. With our expertise, it can be up to 10x faster than in-database processing.
Flexible and Scalable
Support diverse data sources, whether structured, semi-structured, or unstructured data, with an architecture that accommodates any data size.
Cost-Efficient
Rather than investing in scaling up your database or expensive data warehouse solutions, Blendata Lakehouse allows users to achieve more with a lower total cost of ownership (TCO) compared to traditional solutions.
Highlight Features
Import Data
Collect and connect data from multiple sources (replicate or virtualize) in one place, whether from databases, flat files, logs, the cloud, or enterprise databases. It supports all well-known databases such as Oracle, MySQL, Amazon S3, and others, without the need for coding.
Data Preparation
Prepare and link data across platforms from various sources or filter data in datasets with a drag-and-drop function, eliminating the need for coding, to create new datasets or visualizations for your work.
SQL Query
Covering data preparation, transformations, correlations, aggregations, and data exploration. Our user interface enables analysts and engineers to query data using familiar grammar, combining ANSI SQL with Spark SQL functions. It also allows them to survey, manage, or schedule processing jobs for their own data.
AI/ML with Notebook Interface
Provides a familiar experience for data engineers and ML developers with a notebook interface that supports all well-known programming languages, such as Python, R, Scala, and SQL.
Customers Success
Data-Driven Success
