Big Data Analytics (BDA)
Platforms and Tools

A unified analytics engine for large-scale data processing.

Free and open source distributed realtime computation system. Reliably processes unbounded streams of data — doing for realtime processing what Hadoop did for batch processing.

Fast distributed SQL query engine for big data analytics that helps you explore your data universe.

A framework for the distributed processing of large data sets across clusters of computers.

Build stateful applications that process data in real-time from multiple sources including Apache Kafka.

A platform created by the community to programmatically author, schedule and monitor workflows.

A data lake platform for combining different types of data easier and faster.

Open-source storage framework enabling Lakehouse architecture with Spark, PrestoDB, Flink, Trino, and Hive. APIs for Scala, Java, Rust, Ruby, and Python.

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage.

A real-time database to power modern analytics applications at scale.

Stateful computations over data streams — a framework for distributed stream and batch data processing.

Data warehouse software that facilitates reading, writing, and managing large datasets in distributed storage using SQL.

Brings transactions, record-level updates/deletes and change streams to data lakes.

High-performance format for huge analytic tables. Brings the reliability and simplicity of SQL tables to big data.

Open-source distributed event streaming platform for high-performance data pipelines, streaming analytics, data integration, and mission-critical applications.

Open source, distributed Analytical Data Warehouse for Big Data, providing OLAP capability in the big data era.

Open source distributed SQL query engine for interactive analytic queries against data sources of all sizes — gigabytes to petabytes.