Overview
Easily transform all data, anywhere, into meaningful business insights.
Cloudera Data Warehouse enables IT to deliver a cloud-native self-service analytic experience to BI analysts that goes from zero to query in minutes. It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes.
Data Warehouse is fully integrated with streaming, data engineering, and machine learning analytics. It has a consistent framework that secures and provides governance for all of your data and metadata on private clouds, multiple public clouds, or hybrid clouds.
GigaOm Radar for Data Lakes & Lakehouses
Cloudera named a 2024 market leader for data lakehouses.
Use cases
Cloud data reports & dashboards
Instant access to data
Data warehouse optimization
Operations & Events analytics
Research & Discovery Analytics
Cloud data reports & dashboards
Stand up a public cloud data warehouse in minutes.
Quickly make use of data already in the cloud by easily spinning up your data warehouse, connect to your AWS and Azure object storage, and start querying. A unique Burst to Cloud feature moves data and context (security, lineage, governance) from your data center to your choice of public cloud bucket ready to be queried right away.
Instant access to data
Self-service access to any data, anywhere.
Users can provision data warehouses in private or public cloud, identify data sets, and create visualizations independent of central IT. Cloudera Data Warehouse automatically scales up or down as necessary leading to proven price-performance advantages to ensure you stay within budget.
Data warehouse optimization
Increase insight with modern data warehousing.
Migrate difficult workloads, either fully or partially, from traditional data warehouse to Cloudera Data Warehouse. Deploy use cases built on new types of data and accommodate an influx of new users, efficiently and affordably. Battle-tested open source engines such as Impala, Hive LLAP, and Hive on Tez and tools such as Hue and Cloudera Observability provide flexible and fast analytics on structured and unstructured data, together, at scale.
Operations & events analytics
Analyze large amounts of events and time-series data.
It’s nearly impossible for traditional data warehouses to analyze huge volume of events and time-series data originating from machine logs, sensors, and other devices at the edge. Built on Apache Kudu and Druid, Cloudera Data Warehouse—combined with Cloudera DataFlow—delivers innovation in performance, scale, and ease of use to tackle the new reality of fast-moving data with self-service analytics.
Research & discovery analytics
Correlate vast amounts of unstructured data with relational data.
High-quality predictions call for discovery of new correlations, patterns, and insights from vast amounts of unstructured, semi-structured, textual, and relational data. Cloudera Data Warehouse—along with Solr for full-text search—and Cloudera Machine Learning drive insight from all your data sources for more accurate predictions.