Cinchy Platform Documentation
Cinchy v5.0 - v5.5
Cinchy v5.0 - v5.5
  • Data Collaboration Overview
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    • Cinchy Data Sync
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  • Release Notes
    • Release Notes
      • 5.0 Release Notes
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          • Kubernetes Deployment Architecture
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        • Deployment Prerequisites
          • Single Sign-On (SSO) Integration
            • Enabling TLS 1.2
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            • AD Group Integration
      • Kubernetes Deployment Installation
        • Disabling your Kubernetes Applications
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        • Using Self-Signed SSL Certs (Kubernetes Deployments)
        • Deploying the CLI (Kubernetes)
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        • Deploying Connections and the CLI (IIS)
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    • Upgrade Guides
      • Upgrading Cinchy Versions
        • Cinchy Upgrade Utility
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          • v5.1 (Kubernetes)
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        • IIS Upgrades
          • v4.21 (IIS)
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      • Upgrading from v4 to v5
  • Guides for Using Cinchy
    • User Guides
      • Overview of the Data Browser
      • The Admin Panel
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        • Personal Access Tokens
      • Table Features
      • Data Management
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      • Version Management
        • Versioning Best Practices
      • Commentary
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      • Creating Tables
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        • Restoring Tables, Columns, and Rows
        • Formatting Rules
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        • Linking Data
        • Table and Column GUIDs
        • System Tables
      • 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
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      • Enable Data At Rest Encryption
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  • API Guide
    • API Overview
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      • ExecuteCQL
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  • 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
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        • 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)
    • Creating a Dynamic Meta-Form (Using Tables)
    • Creating a Dynamic Meta-Form Example (Using Form Designer)
    • Forms Data Types
    • Adding Links to a Form
    • Rich Text Editing in Forms
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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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