Data Lakehouse


Unified + Simplified Your Big Data & Analytics Platform


All Blended

Centralize all your data for any kind of analytics with simplified, all-in-one data integration, management, analytics, and utilization tools.


Decoupling + Scalable

Says goodbye to big-cost data lakes or traditional unscalable data warehouses, with efficient decoupling of compute & storage using a scalable architecture powered by Blendata's optimized Apache Spark.


Deploy Anywhere

Whether on-premises, in the cloud, or in a hybrid environment. The decision is yours.

Highlight Features


Data Catalog

Support advanced data management such as data compaction, data compression, data lifecycle management (hot-warm-cold), data skipping, predicate push-down, dynamic partition pruning, and physical file partitioning. Additionally, facilitate multi-storage location interlinking and multiple-device data tiering.


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.

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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.