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The Ocient Hyperscale Data Warehouse is a data warehouse for running analytics against very large and complex data sets. It is designed to be cost-effective and flexible in its deployment options. Built using standard ANSI SQL, Ocient does not require users to spend time and money learning unfamiliar programming languages, and with industry-standard interfaces like SQL and JDBC, Ocient makes it easy for organizations to interact with data. Using commodity hardware, Ocient can be deployed on premises in a data center, in the cloud, or as a fully-managed service in the OcientCloud. In addition to being flexible and cost-effective, Ocient is designed to be extremely fast and scalable with large data sets. Traditional relational databases, even those designed for analytics, do not scale from a cost or performance perspective to accommodate extremely large data sets. Big data solutions can scale to use large data sets, but are often expensive, complex, inflexible, and take too long to execute queries. Ocient is designed to give users the interactive analysis capabilities of traditional relational databases at the scale of big data solutions, and with a significantly smaller footprint. This means that queries that used to take hours, or not run at all, now execute in seconds, and systems that used to fill up multiple data center racks, now require up to 90% less space and energy. Ocient also supports real-time analytics, traditional OLAP workloads, geospatial analysis, and in-database machine learning and AI. By enabling users to perform all of these tasks on a single data platform, Ocient eliminates additional data movement and enables organizations to operate at a scale that was previously impossible or impractical.

Key Concepts

Core Ocient concepts and terms needed for a quick start

Install an Ocient System

Installation, Upgrade, System Configuration, Maintenance, and Monitoring of an Ocient System

Connect to Ocient

Connection to Ocient with JDBC and other drivers

Database Administration

Overview of key database administration capabilities like workload management, result set caching, and managing users, groups, and roles

Load Data

Loading and transformation capabilities, managing pipelines, transformation functions, and error handling

Query Ocient

Overview of Ocient data types and the components of a query

Core Elements of an Ocient System

Overview of Ocient System design and architecture
These sections outline the capabilities of Ocient for data ingestion, transformation, and advanced analytics. Ocient SQL supports integrated libraries for geospatial analysis and machine learning tools.

SQL Reference

SQL command, function, operator, and keyword reference including DDL, DCL, and query reference

Connection Driver Reference

Different SQL client connectors

Machine Learning in Ocient

Walkthroughs to deploy various ML models integrated into Ocient

Geospatial Functions

Functions for analyzing geospatial data sets
For information about integrations and connections to third-party applications and tools, see Ocient Integrations. For a detailed explanation of the Compute Adjacent Storage Architecture in Ocient, design principles, storage capabilities, and query engine, see Ocient Architecture. For information on ingesting data using the legacy Loading and Transformation (LAT) functionality, see Ingest Data with Legacy LAT Reference.