SQL Server
Oracle
MySQL
PostgreSQL
Amazon Redshift
Azure SQL Database
DBT
Google Big Query
IBM DB2
MariaDB
SAP HANA
Snowflake
SQLite
Teradata
Vertica
Data dictionary tools for NoSQL
List of tools that enable design and building of data dictionaries .
Data Dictionary is a set of important information about data used within an organization (metadata). This information includes names, definitions, and attributes about data, owners, and creators of assets. Data Dictionary tools provide insights into meaning and purposes of data elements. They add useful aliases about the scope and characteristics of data elements, as well as the rules for their usage and application.
Dataedo
Dataedo allows you to connect and scan metadata from multiple sources and build data dictionary automatically in a couple of minutes.
| Desktop/Cloud: | Desktop |
|---|---|
| ER Diagram: |
|
| Export: | HTML,MS Excel,PDF |
| Metadata stored in: | Documentation repository/file |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | ER diagrams, metadata repository, schema change tracking, organizing with modules, documenting missing FKs, custom fields, description suggestions, documentation progress tracking, rich text with images |
| Runs on: (for desktop): | Mac OS,Windows |
DbSchema
DbSchema facilitates to design, document and manage SQL and NoSQL databases. It is an intuitive designer for complex databases. It allows editing tables or columns directly in the layout, by double-clicking them.
| Desktop/Cloud: | Desktop |
|---|---|
| ER Diagram: |
|
| Export: | HTML,PDF |
| Metadata stored in: | Database metadata |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | Entity relationship diagram, Reverse engineer schema from database, Relational data browse, SQL editor |
| Runs on: (for desktop): | Linux,Mac OS,Windows |
erwin Data Modeler
erwin Data Modeler (erwin DM) is a data modeling tool used to find, visualize, design, deploy and standardize high-quality enterprise data assets. It helps to create & maintain sound relational database designs and data dictionary of those models.
| Desktop/Cloud: | Desktop |
|---|---|
| ER Diagram: |
|
| Export: | |
| Metadata stored in: | Database metadata |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | Data modeling, Entity relation diagram, Forward & Reverse Engineering |
| Runs on: (for desktop): | Linux,Mac OS,Windows |
Alation Data Catalog
Alation data dictionary defines and describes technical data terms. Data terms could be database schemas, tables, or columns. Once connected to data sources, Alation automatically indexes data and populates catalog pages. For example, a column catalog page shows the technical column name, a business title name, the data type, and popularity. Additional context can be added to the data dictionary, for shared understanding across the organization.
| Desktop/Cloud: | Cloud |
|---|---|
| ER Diagram: |
|
| Export: | MS Excel |
| Metadata stored in: | - |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | ML auto-suggested business glossary terms |
| Runs on: (for desktop): | - |
Ataccama Metadata Management & Data Catalog
Ataccama Data Catalog & Business Glossary tool provides automatic mapping of terms to real data sources in the Data Catalog during profiling, ensuring the Data Catalog is always up-to-date and synced with the Business Glossary.
| Desktop/Cloud: | Desktop |
|---|---|
| ER Diagram: |
|
| Export: | CSV,MS Excel,XML |
| Metadata stored in: | Program respository |
| Commercial: | Commercial |
| Free edition: |
|
| Notable features: | Automated Mapping of Business Terms, Up-to-date Business Glossary, Data Discovery on Multiple Sources |
| Runs on: (for desktop): | Windows |
Key functionality of Data Dictionary tools is to give users the ability to document data. Moreover, very important is the possibility to create a collection of multiple repositories, based on different system engines. For a better understanding of the data, some tools allow visualization of the data structure using ERD (Entity-Relationship Diagrams).
From the organization's point of view, a community module within a data dictionary tool proves to be useful. It facilitates the proper information flow, as well as provides sharing opinions on specific objects among the members of an organization.
Nowadays, data discovery and understanding becomes crucial for proper organization performance. There are many benefits to using Data Dictionaries, such as:
• helps avoid data inconsistencies problems,
• it allows introducing unified nomenclature used in the project,
• Make data searchable, and understandable,
• Create a single source of truth about the data from different repositories,
The prepared list includes simple, open-source data dictionaries as well as more advanced software.