Welcome to HurricaneDB
Last updated
Last updated
HurricaneDB is a real-time distributed OLAP datastore, purpose-built to provide ultra-low-latency analytics, even at extremely high throughput.
It can ingest directly from streaming data sources - such as Apache Kafka and Amazon Kinesis - and make the events available for querying instantly. It can also ingest from batch data sources such as Hadoop HDFS, Amazon S3, Azure ADLS, and Google Cloud Storage.At the heart of the system is a columnar store, with several smart indexing and pre-aggregation techniques for low latency. This makes HurricaneDB the most perfect fit for user-facing real-time analytics. At the same time, HurricaneDB is also a great choice for other analytical use-cases, such as internal dashboards, anomaly detection, and ad-hoc data exploration.
Getting Started
Use HurricaneDB to ingest data, index ...
Making Contributing
Check out our CONTRIBUTING guide ...
Column-oriented
A column-oriented database with various compression schemes such as Run Length, Fixed Bit Length
Pluggable indexing
Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index, StarTree Index, Bloom Filter ...
Optmize QE
Ability to optimize query/execution plan based on HurricaneDB queries and segment metadata
Real-time Ingestion
Near real-time ingestion from streams such as Kafka, Kinesis and batch ingestion from sources such as Hadoop, S3, Azure ...
SQL-like Language
SQL-like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data
