![]() ![]() They also utilize DBMS data dictionary for metadata storage, provide a (more or less) convenient editor of comments, and allow you to export documentation to a usable format, such as HTML or PDF. Those tools are similar to the above combination but are designed for the purpose of the documentation of the database. Database documentation toolsĪnother category of tools you utilize is database documentation tools. Oracle + Oracle SQL Developer + Generate DB Doc optionĮditing table comments in SQL Server Management Studio (SSMS)Įditing table comments in Oracle SQL Developerĭata Dictionary export Oracle SQL Developer 3.MySQL + MySQL Workbench + data dictionary plugin.Risk of altering of the schema (updating a comment in MySQL alters entire table schema).Require write access to database schema (no offline work).Impacts database schema, not always desirable (for instance when the vendor doesn't allow for alterations of the database).No global data dictionary, documentation is scattered across databases.Heavy limitations in the scope of metadata, only fields and elements already present in the data dictionary.Metadata with data, directly in the database.So to summarize, the stack looks like this: This can be a feature built into a database GUI or a standalone tool. Then such a data dictionary can be shared with database documentation generator that generates HTML, PDF or another format for easy access. Comments can be edited with many database management tools that are available for all databases. Some teams choose to store their metadata in those structures. ![]() Most DBMSs also have the ability to annotate data dictionary elements (called comments, descriptions or extended properties). All database engines (DBMS) have a so-called active data dictionary - an inventory of their data structures. DBMS + GUI tool (+ Generator)Īnother very popular approach is to make use of DBMS built-in data dictionary. Population, and especially maintenance, can be a nightmareĭata Dictionary in Excel spreadsheet 2.But the maintenance is the hard part - making sure it's up to date with the source can be a laborious task. Those are generic tools for creating and collaborating on documents that most people are familiar with.Ĭreating a data dictionary can be as easy as extracting a list of columns from a database using a query and pasting the results into a spreadsheet for people to fill in the details. I think the most obvious tool, perhaps good for a proof of concept, is a spreadsheet software or word processor (preferably the former). In this article, I will present you with different types of tools that you can use to build and share such an inventory. A data dictionary is a definition of tables/files and columns/fields in a data set (database, data warehouse or data lake). ![]() Advanced features are available in the commercial edition.Now, when accessing company data held in databases is becoming critical, organizations are looking for tools that will allow them to build and share data dictionary of their data sources. ![]() Optimize your data model by using advanced features such as test data generation, schema compare, and schema synchronizationįeature limited free version is available for download. Generate and share the data Model documentation with your team. ERBuilder Data Modeler is a GUI data modeling tool that allows developers to visualize, design, and model databases by using entity relationship diagrams and automatically generates the most popular SQL databases. ![]()
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