Get Started with the Ocient Hyperscale Data Warehouse
is a data warehouse for running analytics against the world’s largest time series data sets. It is designed to be flexible in its deployment options and cost-effective. does not require knowledge of unfamiliar programming languages that require additional learning time and cost. With industry-standard interfaces like SQL and JDBC, Ocient makes it easy for organizations to interact with data in Ocient. Running on commodity hardware, Ocient can run on-premise in an organization’s data center, in the cloud, or as a fully managed service by Ocient. While flexible and cost-effective, Ocient is also designed to be extremely fast and scalable with time series data sets larger than 100 terabytes.
Traditional relational databases, even those designed for analytics, don’t scale from a cost or performance perspective to petabyte and exabyte-sized data sets. Big data solutions can scale to large data sets but are often complex, inflexible, and require too much time to execute queries. Ocient is designed to give users the interactive analysis of traditional relational databases at the scale of big data solutions. This means that queries that used to take hours, or not run at all, now execute in seconds. Ocient achieves this performance through its distributed architecture, where storage and computing are collocated.
The collocation of storage and computing also allows Ocient to perform other valuable operations on the data stored in the data warehouse, such as machine learning and geospatial analysis. By executing machine learning and geospatial analysis within the data warehouse, Ocient eliminates additional data movement and enables organizations to run machine learning and geospatial analysis at a scale that was previously impossible or impractical.
Core Ocient concepts and terms needed for a quick start
Installation, Upgrade, System Configuration, Maintenance, and Monitoring of an Ocient System
Connection to Ocient with JDBC and other drivers
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
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 command, function, operator, and keyword reference including DDL, DCL, and query reference
Different SQL client connectors
Walkthroughs to deploy various ML models integrated into Ocient
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 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.