Cinchy Platform Documentation
Cinchy v5.6
Cinchy v5.6
  • Data Collaboration Overview
  • Release Notes
    • Release Notes
      • 5.0 Release Notes
      • 5.1 Release Notes
      • 5.2 Release Notes
      • 5.3 Release Notes
      • 5.4 Release Notes
      • 5.5 Release Notes
      • 5.6 Release Notes
  • Getting Help
  • Cinchy Glossary
  • Frequently Asked Questions
  • Deployment Guide
    • Deployment Installation Guides
      • Deployment Planning Overview and Checklist
        • Deployment Architecture Overview
          • Kubernetes Deployment Architecture
          • IIS Deployment Architecture
        • Deployment Prerequisites
          • Single Sign-On (SSO) Integration
            • Enabling TLS 1.2
            • Configuring ADFS
            • AD Group Integration
      • Kubernetes Deployment Installation
        • Disabling your Kubernetes Applications
        • Changing your File Storage Configuration
        • Configuring AWS IAM for Connections
        • Using Self-Signed SSL Certs (Kubernetes Deployments)
        • Deploying the CLI (Kubernetes)
      • IIS Deployment Platform Installation
    • Upgrade Guides
      • Upgrading Cinchy Versions
        • Cinchy Upgrade Utility
        • Kubernetes Upgrades
          • v5.1 (Kubernetes)
          • v5.2 (Kubernetes)
          • v5.3 (Kubernetes)
          • v5.4 (Kubernetes)
          • v5.5 (Kubernetes)
          • v5.6 (Kubernetes)
          • Upgrading AWS EKS Kubernetes Version
          • Updating the Kubernetes Image Registry
          • Upgrading AKS (Azure Kubernetes Service)
        • IIS Upgrades
          • v4.21 (IIS)
          • v4.x to v5.x (IIS)
          • v5.1 (IIS)
          • v5.2 (IIS)
          • v5.3 (IIS)
          • v5.4 (IIS)
          • v5.5 (IIS)
          • v5.6 (IIS)
      • Upgrading from v4 to v5
  • Guides for Using Cinchy
    • User Guides
      • Overview of the Data Browser
      • The Admin Panel
      • User Preferences
        • Personal Access Tokens
      • Table Features
      • Data Management
      • Queries
      • Version Management
        • Versioning Best Practices
      • Commentary
    • Builder Guides
      • Best Practices
      • Creating Tables
        • Attaching Files
        • Columns
        • Data Controls
          • Data Entitlements and Access Controls
          • Data Erasure
          • Data Compression
        • Formatting Rules
        • Indexing and Partitioning
        • Linking Data
        • Table and Column GUIDs
        • System Tables
      • Deleting Tables
        • Restoring Tables, Columns, and Rows
      • Saved Queries
      • CinchyDXD Utility
        • Building the Data Experience (CinchyDXD)
        • Packaging the Data Experience (CinchyDXD)
        • Installing the Data Experience (CinchyDXD)
        • Updating the Data Experience (CinchyDXD)
        • Repackaging the Data Experience (CinchyDXD)
        • Reinstalling the Data Experience (CinchyDXD)
      • Multi-Lingual Support
      • Integration Guides
    • Administrator Guide
    • Additional Guides
      • Monitoring and Logging on Kubernetes
        • Grafana
        • Opensearch Dashboards
          • Setting up Alerts
        • Monitoring via ArgoCD
      • Maintenance
      • System Properties
      • Enable Data At Rest Encryption
      • MDQE
      • Application Experiences
        • Network Map
          • Custom Node Results
          • Custom Results in the Network Map
        • Setting Up Experiences
  • API Guide
    • API Overview
      • API Authentication
      • API Saved Queries
      • ExecuteCQL
      • Webhook Ingestion
  • CQL
    • The Basics of CQL
      • CQL Examples
      • CQL Functions Master List
      • CQL Statements Overview
        • Cinchy DML Statements
        • Cinchy DDL Statements
      • Cinchy Supported Functions
        • Cinchy Functions
        • Cinchy System Values
        • Cinchy User Defined Functions
          • Table-Valued Functions
          • Scalar-Valued Functions
        • Conversion Functions
        • Date and Time Types and Functions
          • Return System Date and Time Values
          • Return Date and Time Parts
          • Return Date and Time Values From Their Parts
          • Return Date and Time Difference Values
          • Modify Date and Time Values
          • Validate Date and Time Values
        • Logical Functions
        • Mathematical Functions
        • String Functions
        • Geometry and Geography Data Type and Functions
          • OGC Methods on Geometry & Geography Instances
          • Extended Methods on Geometry & Geography Instances
        • Full Text Search Functions
        • Connections Functions
        • JSON Functions
  • Meta Forms
    • Introduction to Meta-Forms
    • Meta-Forms Deployment Installation Guide
      • Deploying Meta-Forms (Kubernetes)
      • Deploying Meta-Forms (IIS)
    • Forms Data Types
    • Meta-Forms Builders Guides
      • Creating a Dynamic Meta-Form (Using Tables)
      • Creating a Dynamic Meta-Form Example (Using Form Designer)
      • Adding Links to a Form
      • Rich Text Editing in Forms
  • Data Syncs
    • Getting Started with Data Syncs
    • Installation & Maintenance
      • Prerequisites
      • Installing Connections
      • Installing the Worker/Listener
      • Installing the CLI and the Maintenance CLI
    • Building Data Syncs
      • Types of Data Syncs
      • Common Design Patterns
      • Sync Behaviour
      • Columns and Mappings
        • Calculated Column Examples
      • Listener Configuration
      • Advanced Settings
        • Filters
        • Parameters
        • Auth Requests
        • Request Headers
        • Post Sync Scripts
        • Pagination
      • Batch Data Sync Example
      • Real-Time Sync Example
      • Scheduling a Data Sync
      • Connection Functions
    • CLI Commands List
    • Error Logging and Troubleshooting
    • Supported Data Sync Sources
      • Cinchy Event Broker/CDC
        • Cinchy Event Broker/CDC XML Config Example
      • Cinchy Table
        • Cinchy Table XML Config Example
      • Cinchy Query
        • Cinchy Query XML Config Example
      • Copper
      • DB2 (Query and Table)
      • Dynamics 2015
      • Dynamics
      • DynamoDB
      • File Based Sources
        • Binary File
        • Delimited File
        • Excel
        • Fixed Width File
        • Parquet
      • Kafka Topic
        • Kafka Topic Example Config
        • Apache AVRO Data Format
      • LDAP
      • MongoDB Collection
        • MongoDB Collection Source Example
      • MongoDB Collection (Cinchy Event Triggered)
      • MS SQL Server (Query and Table)
      • ODBC Query
      • Oracle (Query and Table)
      • Polling Event
        • Polling Event Example Config
      • REST API
      • REST API (Cinchy Event Triggered)
      • SAP SuccessFactors
      • Salesforce Object (Bulk API)
      • Salesforce Platform Event
      • Salesforce Push Topic
      • Snowflake
        • Snowflake Source Example Config
      • SOAP 1.2 Web Service
    • Supported Data Sync Destinations
      • Cinchy Table
      • DB2 Table
      • Dynamics
      • Kafka Topic
      • MongoDB Collection
      • MS SQL Server Table
      • Oracle Table
      • REST API
      • Salesforce Object
      • Snowflake Table
      • SOAP 1.2 Web Service
    • Supported Real-Time Sync Stream Sources
      • Cinchy Event Broker/CDC
      • Data Polling
      • Kafka Topic
      • MongoDB
      • Salesforce Push Topic
      • Salesforce Platform Event
  • Other Resources
    • Angular SDK
    • JavaScript SQK
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  • 1. Overview
  • 2. Best Practices

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  1. Guides for Using Cinchy
  2. User Guides
  3. Version Management

Versioning Best Practices

This page outlines some best practices for versioning.

1. Overview

This page details a few best practices concerning version history in Cinchy. These recommendations are important because they can help:

  • Minimize your database bloat/size.

  • Make it easier to parse through version history when there aren't hundreds of redundant records.

2. Best Practices

  • When doing any type of update statement, it is best practice to include an opposite “where” clause to avoid creating unnecessary history for unchanged values.

    • For example, if your update was “set name to Marc”, you would include a “where name does not already equal Marc”. Doing so prevents a redundant update in your version history.

UPDATE
	[Contacts].[Employees] 
SET [Name] = Marc
WHERE [Name] != Marc
  • When writing an update statement, run it more than once. If it results in an update each time, return to your query and troubleshoot.

    • This is especially relevant anywhere the statement can be run repeatedly, such as in APIs or Post Sync Scripts.

  • In data syncs, ensure that your data types are matched properly.

    • For example, if the source is text and the target is data, even if the values are the same, it will update and create unnecessary version history.

  • When performing a data sync, run it more than once. If it creates an update each time, return to your configuration and troubleshoot.

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Last updated 2 years ago

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