---
title: Key Concepts
slug: yhatP0NMlXT6T_kuoJmWi
description: Learn the core concepts behind Ocient high-performance data warehouse, including its architecture, scalability, and analytics capabilities designed for large-scale, complex datasets.
docTags: 
createdAt: Wed Jan 03 2024 18:40:57 GMT+0000 (Coordinated Universal Time)
updatedAt: Fri Apr 10 2026 17:48:12 GMT+0000 (Coordinated Universal Time)
---

The Ocient Data Intelligence Platform™ is a real-time OLAP datastore designed for running analytics against large time series data sets. The Ocient® System operates in compliance with the ANSI standard for SQL.

The Ocient System includes:

- **Ultra-fast query speeds** for analytics on hyperscale data sets.
- **Scalability** for cost and performance on a system built with commodity hardware.
- **Flexible deployment&#x20;**&#x66;or running on premises, in the cloud, or as an Ocient-managed service.
- **Robust functionality&#x20;**&#x66;or DDL, geospatial (OcientGeo™), and machine learning (OcientML™).
- **Data movement** at scale for ETL and ELT ingestion and operations.

## The Ocient System

The Ocient System is based on Compute Adjacent Storage Architecture® (CASA), which collocates NVMe drive storage with the system compute resources to optimize performance. This design keeps records near and accessible for computation without a separate storage layer, which avoids many common bottlenecks for database engines, such as limits on network capacity or processing throughput. The design achieves superior query performance when it operates on trillions of rows of data.

To learn more about the design principles behind the Ocient System, see [Ocient Architecture](<././Ocient Architecture.md>).

## Deployment

Ocient is designed for flexible deployment for unique use scenarios that include:&#x20;

- OcientCloud® — A cloud deployment managed by Ocient Support. This option uses performance-tested hardware and network infrastructure.&#x20;
- Public Cloud — Installation on third-party cloud providers, including Amazon® Web Services℠ (AWS℠) and Google® Cloud™.
- On premises — A self-managed option for hosting Ocient in your own data center.&#x20;

## System Nodes

Ocient is a distributed system consisting of interconnected nodes within clusters, which together form the data warehouse. The Ocient System designates nodes for these system roles:

- **SQL Nodes** — Parse incoming SQL statements and administer commands throughout the system. These nodes serve as the interface for system and database administration.
- **Loader Nodes&#x20;**—  Manage ETL ingestion from batch or streaming sources and index data for optimized performance.
- **Foundation Nodes&#x20;**— Store data and perform the bulk of query processing. Foundation Nodes perform as much query processing as possible on their stored data before interacting with other nodes.

![Ocient architecture diagram that shows the relationship between data sources, loading and transformation of the data, and data storage](https://api.archbee.com/api/optimize/zLEvgH2ISPR6In81OlyIL/fIe7Bg48LMF0733sBnNo3_archnodes5.png)

Understanding nodes and their roles in an Ocient System is most useful for system setup, administration, and maintenance. For details about nodes, see [Ocient Architecture](<././Ocient Architecture.md>).  However, the Ocient System makes it easy to load and query data without knowing these details.

## Data Types

The Ocient Data Intelligence Platform, the functions, and the indexes use only native SQL data types to optimize storage and performance. Supported data types include common SQL scalar types and complex types such as IP, arrays, tuples, and geospatial. For details about supported data types, see [Understanding Data Types](<././Query Ocient/Understanding Data Types.md>).&#x20;

## Loading

The Ocient System can load data for an end-to-end flow from file or streaming sources, including common sources such as:

- Apache® Kafka®
- AWS S3
- Apache® Hadoop® Distributed File System (HDFS)

For all the source and format options, Ocient uses pipelines to control ingestion. You can control pipelines using DDL commands, API on Loader Nodes, or a command-line interface. You can transform data during loading using SQL functions.&#x20;

Loading ingestion throughput can scale as needed based on the Ocient architecture.&#x20;

For details, see [Load Data](<././Load Data.md>).&#x20;

## Query Processing

The design of the Ocient architecture minimizes the amount of on-disk data that must be read and processed to execute a query. To do this, the system compiles a custom I/O pipeline for each data segment relevant to a query. These custom pipelines leverage any keys or indexes to improve throughput. &#x20;

To learn more about query processing, see [Query Performance Optimizations](<././Ocient Architecture/Query Performance Optimizations.md>).&#x20;

### Ocient Indexing

An Ocient datastore can use multiple layers of indexing to facilitate query performance. Using these indexes is pivotal to optimizing query performance for large data sets.

You can apply indexes using basic DDL statements that do not require deep knowledge of the internal system or data set. You also have some ability to customize indexes for their specific use cases.&#x20;

Indexes are divided into two main categories.

::::WorkflowBlock
:::WorkflowBlockItem
### **Segment Keys**

These indexes require no additional storage and usually should be deployed on every table. Segment keys operate by accessing data from the partitioned data segments to quickly filter rows without I/O processing.&#x20;

Segment keys include:

- **Time Key** — A segment key that partitions data based on a time-series data column.
- **Clustering Key&#x20;**— A series of columns that are frequently queried together. The system subdivides these segments on disk for faster reference.

For more information on segment keys, see [TimeKeys and Clustering Keys](<././Database Administration/Schema Design/TimeKeys and Clustering Keys.md>).
:::

:::WorkflowBlockItem
### **Secondary Indexes**

When deployed precisely, Ocient secondary indexes can dramatically reduce the time for queries to run on large data sets.&#x20;

Ocient supports secondary indexes for these data categories:

- **Numeric**
- **String**
- **Partial string**
- **Geospatial**

For more information, see [Secondary Indexes](<././Database Administration/Schema Design/Secondary Indexes.md>).&#x20;
:::
::::

## Connecting to Ocient

Ocient provides SQL access to its database using industry-standard interfaces:

- JDBC
- pyocient, a Python®-based driver for Ocient.
- HTTP Query API, a REST-based interface for executing SQL statements.

End users can query and analyze data in Ocient without understanding the organization, nodes, networking, or other parts of the system architecture.

For more information, see [Connect to Ocient](<././Connect to Ocient.md>).&#x20;

### Integrations

Ocient supports integration with various third-party tools for database administration, business intelligence, and system monitoring.

For details about supported third-party tools, see [Ocient Integrations](<././Connect to Ocient/Ocient Integrations.md>).&#x20;

## Machine Learning

The Ocient System includes OcientML™ functionality for training and executing machine learning models directly within SQL. OcientML builds on native linear algebra support, including first-class matrix data types and operations such as matrix arithmetic, inversion, and eigenvalue decomposition.

You can create models using the `CREATE MLMODEL` statement and execute them as scalar functions in queries. Ocient supports a broad suite of models spanning regression, classification, clustering, dimensionality reduction, ensemble methods, and neural networks to address a wide range of analytical use cases.

For details, see [Machine Learning in Ocient](<././Analysis in Ocient/Machine Learning in Ocient.md>).

## Resilience to Hardware Failure

The Ocient System uses erasure coding to organize and compute parity blocks so the system is fault-tolerant and can rebuild missing data. This failsafe does not require redundant copies of data, meaning that storage requirements are minimal.

## Security

As a unified platform, Ocient helps keep data secure by consolidating security capabilities and reactions in one place with a suite of auditing and monitoring tools. Ocient supports these security standards:

- **Data Encryption:** Optional through TLS/SSL protocols.
- **Security Compliance:&#x20;**&#x41;udited and certified SOC 2 Type 2.
- **Monitoring**: Log-level monitoring and alerts on key system information.
- **Access Controls**: SSO, role-based, and system-level access controls are available.

## Related Links

[Core Elements of an Ocient System](<././Ocient Architecture/Core Elements of an Ocient System.md>)

[Ocient Architecture](<././Ocient Architecture.md>)

[Ocient Simulator](<././Ocient Simulator.md>)

[Connect to Ocient](<././Connect to Ocient.md>)

## Related Videos

[At the Whiteboard with Ocient: Compute Adjacent Storage Architecture™](https://www.youtube.com/watch?v=7cv0hr7f1fg)

[At the Whiteboard with Ocient: SQL at Scale](https://www.youtube.com/watch?v=G64g7U6tlCQ)

[At the Whiteboard with Ocient: Indexing at Hyperscale](https://youtu.be/0M90mUSsiLo)





