Blendata Cloud

A cloud-based Big Data analytics platform.

Flexible and Scalable Self-Service Big Data Analytics

Blendata Cloud offers a highly adaptable and scalable platform, empowering users with self-service capabilities for big data analytics, designed to evolve alongside changing business demands.

Cost-Efficient Pay-Per-Use Model with Full Analytics Capabilities

Featuring a Pay-Per-Use pricing model, Blendata Cloud grants comprehensive access to Big Data and Advanced Analytics tools, ensuring a cost-effective solution tailored to business needs.

High-Performance Data Lakehouse Powered by Apache Spark

With a Data Lakehouse framework powered by Apache Spark, Blendata Cloud accelerates data processing and analytics for both structured and unstructured datasets, supporting rapid queries and robust data integration to fuel informed decision-making.

Hybrid Environment and Vendor Independence for Versatile Deployment

Supporting a hybrid environment with vendor-agnostic capabilities, Blendata Cloud enables flexible deployment options, allowing organizations to choose the infrastructure that best suits their operational requirements.

Open Platform Supporting Seamless Integration and Innovation

As an open platform, Blendata Cloud facilitates seamless integration with third-party tools, creating an ecosystem that encourages the fusion of diverse data sources and technologies to drive customized solutions and foster innovation.

To get started with our platform, contact us for a special package of the Blendata Enterprise License under the Bring Your Own License (BYOL) model. This package offers flexible options, including both subscription and pay-per-use plans, along with IaaS services from Azure and AWS.

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Highlight Features

Unified and Simplified Platform, Powered by Best in Class Technologies.

Unify all big data & advanced analytics capabilities into one platform from data integration, data management and security, processing and analytics, to data utilization, Simplify all features into a single interface with low-code capability, All of these Lakehouse features powered by best-in-class technologies like Apache Spark and Delta Lake.

Managed Diverse Data Sources Transformed into Data Lakehouse

Integrate data from various sources (including databases, files, logs, cloud, and enterprise databases), such as *Oracle, MySQL, Amazon S3, etc., effortlessly through built-in connectors with multiple advanced techniques such as Changed data capture, all without coding.

Managing Data with Enterprise Grade Security and Governance

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

Writing Pyspark, R, or Scala through Notebook Interface

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.

SQL Analytics

Offering a versatile data user interface like SQL editor with support for ANSI SQL and Spark SQL, allowing analysts and engineers to manage SQL warehouse tasks like correlations, aggregation, data exploration, and job scheduling.

Drag and Drop Data Preparation

Easily link, filter, and create datasets from diverse sources using drag-and-drop, without coding. Suitable for super-users and non-technical persons.

Low-Code Workflow Management

Automating efficient data pipeline operation, from ingestion, SQL script, and Notebook, to ML/AI utilization. With low-code workflow orchestration, users can easily schedule all the workloads with ease without the need to write the complex Python DAG or any script which comes with jobs monitoring and management console as well., This empowers organizations to perform complicated operations and automation tasks with minimal effort.

Built-in Dashboards and Visualization

Easily create custom charts and visualizations from analyzed data, featuring filtering, drill-down options, and secure sharing within your organization via dashboard-style projects.

Connect with Any 3rd Parties Application with an Open Standard API

All data and features can be connected through standard REST API or ODBC/JDBC (Spark). Supported all external 3rd parties applications like BI tools such as Tableau.

No Vendor Lock-In

With open technologies that we chose like Apache Spark as our main engine, or big data file formats like Parquet and Delta Lake. It's both powerful and easy to develop, integrate, or migrate data and workloads to other platforms with minimal effort. This stands in contrast to proprietary technologies that restrict customer data and workloads within their ecosystem.