Product Docs
  • What is Dataworkz?
  • Getting Started
    • What You Will Need (Prerequisites)
    • Create with Default Settings: RAG Quickstart
    • Custom Settings: RAG Quickstart
    • Data Transformation Quickstart
    • Create an Agent: Quickstart
  • Concepts
    • RAG Applications
      • Overview
      • Ingestion
      • Embedding Models
      • Vectorization
      • Retrieve
    • AI Agents
      • Introduction
      • Overview
      • Tools
        • Implementation
      • Type
      • Tools Repository
      • Tool Execution Framework
      • Agents
      • Scenarios
      • Agent Builder
    • Data Studio
      • No-code Transformations
      • Datasets
      • Dataflows
        • Single Dataflows:
        • Composite dataflows:
        • Benefits of Dataflows:
      • Discovery
        • How to: Discovery
      • Lineage
        • Features of Lineage:
        • Viewing a dataset's lineage:
      • Catalog
      • Monitoring
      • Statistics
  • Guides
    • RAG Applications
      • Configure LLM's
        • AWS Bedrock
      • Embedding Models
        • Privately Hosted Embedding Models
        • Amazon Bedrock Hosted Embedding Model
        • OpenAI Embedding Model
      • Connecting Your Data
        • Finding Your Data Storage: Collections
      • Unstructured Data Ingestion
        • Ingesting Unstructured Data
        • Unstructured File Ingestion
        • Html/Sharepoint Ingestion
      • Create Vector Embeddings
        • How to Build the Vector embeddings from Scratch
        • How do Modify Existing Chunking/Embedding Dataflows
      • Response History
      • Creating RAG Experiments with Dataworkz
      • Advanced RAG - Access Control for your data corpus
    • AI Agents
      • Concepts
      • Tools
        • Dataset
        • AI App
        • Rest API
        • LLM Tool
        • Relational DB
        • MongoDB
        • Snowflake
      • Agent Builder
      • Agents
      • Guidelines
    • Data Studio
      • Transformation Functions
        • Column Transformations
          • String Operations
            • Format Operations
            • String Calculation Operations
            • Remove Stop Words Operation
            • Fuzzy Match Operation
            • Masking Operations
            • 1-way Hash Operation
            • Copy Operation
            • Unnest Operation
            • Convert Operation
            • Vlookup Operation
          • Numeric Operations
            • Tiles Operation
            • Numeric Calculation Operations
            • Custom Calculation Operation
            • Numeric Encode Operation
            • Mask Operation
            • 1-way Hash Operation
            • Copy Operation
            • Convert Operation
            • VLookup Operation
          • Boolean Operations
            • Mask Operation
            • 1-way Hash Operation
            • Copy Operation
          • Date Operations
            • Date Format Operations
            • Date Calculation Operations
            • Mask Operation
            • 1-way Hash Operation
            • Copy Operation
            • Encode Operation
            • Convert Operation
          • Datetime/Timestamp Operations
            • Datetime Format Operations
            • Datetime Calculation Operations
            • Mask Operation
            • 1-way Hash Operation
            • Copy Operation
            • Encode Operation
            • Page 1
        • Dataset Transformations
          • Utility Functions
            • Area Under the Curve
            • Page Rank Utility Function
            • Transpose Utility Function
            • Semantic Search Template Utility Function
            • New Header Utility Function
            • Transform to JSON Utility Function
            • Text Utility Function
            • UI Utility Function
          • Window Functions
          • Case Statement
            • Editor Query
            • UI Query
          • Filter
            • Editor Query
            • UI Query
      • Data Prep
        • Joins
          • Configuring a Join
        • Union
          • Configuring a Union
      • Working with CSV files
      • Job Monitoring
    • Utility Features
      • IP safelist
      • Connect to data source(s)
        • Cloud Data Platforms
          • AWS S3
          • BigQuery
          • Google Cloud Storage
          • Azure
          • Snowflake
          • Redshift
          • Databricks
        • Databases
          • MySQL
          • Microsoft SQL Server
          • Oracle
          • MariaDB
          • Postgres
          • DB2
          • MongoDB
          • Couchbase
          • Aerospike
          • Pinecone
        • SaaS Applications
          • Google Ads
          • Google Analytics
          • Marketo
          • Zoom
          • JIRA
          • Salesforce
          • Zendesk
          • Hubspot
          • Outreach
          • Fullstory
          • Pendo
          • Box
          • Google Sheets
          • Slack
          • OneDrive / Sharepoint
          • ServiceNow
          • Stripe
      • Authentication
      • User Management
    • How To
      • Data Lake to Salesforce
      • Embed RAG into your App
  • API
    • Generate API Key in Dataworkz
    • RAG Apps API
    • Agents API
  • Open Source License Types
Powered by GitBook
On this page
  • Prerequisite
  • Creating Oracle Configuration in Dataworkz
  • Datatypes Supported
  1. Guides
  2. Utility Features
  3. Connect to data source(s)
  4. Databases

Oracle

PreviousMicrosoft SQL ServerNextMariaDB

Last updated 10 months ago

This document describes the Dataworkz connector configuration required to access Oracle database.

Prerequisite

You need to allow Dataworkz IP address for access to Oracle Database. This process depends upon the mode of Oracle deployment. Dataworkz supports the following :

  • AWS

  • Azure

  • GCS

  • Standalone

AWS

For RDS follow the steps listed below.

  • Login to AWS console

  • Goto RDS -> Databases

  • Select the Oracle instance

  • Goto Security -> VPC security groups and select the appropriate security groups

  • Click the appropriate security group from the list

  • Click "Edit Inbound Rules"

  • Click "Add Rules"

  • Select "Oracle RDS" from the Type dropdown

  • Enter the database port

  • Enter "IP" of the Dataworkz platform nat gateway. This is the IP of Dataworkz platform nat gateway and can be viewed by following the steps provided below.

    • Login to Dataworkz Application

    • Goto Configuration by clicking the gear icon at top right of the screen

    • From left menu select Security -> Deployment Details

    • Copy the cluster IP and enter the same in the "IP" field in the above screen

  • Click "Save rules"

Creating Oracle Configuration in Dataworkz

  1. Login to Dataworkz Application

  2. Goto Configuration -> Databases -> Oracle

  3. Click the + icon to add a new configuration

  4. Enter name of the database configuration in the above screen

  5. Enter Host database server URL

  6. Enter the database server Port

  7. Enter the User name

  8. Enter the Password

  9. Enter the deployment type (On premise / AWS / Azure / Google Cloud Platform)

  10. Select if TLS/SSL needs to be used

  11. Click Test Connection

    1. If successful click Save to add the connector

Datatypes Supported

Dataworkz supports the following Oracle datatypes

  • VARCHAR2

  • NVARCHAR2

  • NUMBER

  • FLOAT

  • LONG

  • DATE

  • BINARY_FLOAT

  • BINARY_DOUBLE

  • TIMESTAMP - fractional support for second from 0 to 6 digits

  • CHAR

  • NCHAR

  • CLOB