TapView Vs MongoDB Relational Migrator (RM)

Jan 02,2025

In today’s fast-paced, data-driven world, businesses need real-time access to accurate data for faster decision-making. Migrating data from relational databases to MongoDB provides significant benefits like enhanced query performance, scalability, and real-time insights. MongoDB’s document-based model is perfect for handling large-scale data and delivering high-speed queries. Real-time materialized views in MongoDB are crucial as they store precomputed query results, ensuring data is always fresh and improving read performance.

TapView and MongoDB Relational Migrator (RM) are two of the most popular and powerful tools for real-time data migration and synchronization from RDBMS. TapView excels in creating real-time materialized views and integrating data from multiple sources—relational databases to MongoDB/Atlas, making it ideal for both complex and simple use cases.

MongoDB RM is a robust solution designed mostly for one time database migration from RDBMS to MongoDB.

What is TapView?

TapView, is a tool designed for real-time heterogeneous data synchronization and creating materialized views from relational databases (like PostgreSQL, MySQL, Oracle, SQL Server, eg..) to MongoDB/Atlas. It ensures these materialized views are updated in real-time, keeping the data in MongoDB synchronized with the source databases using the built-in CDC (Change Data Capture) feature.

A key feature of TapView is its ability to integrate data from multiple relational databases into a single materialized view. TapView also includes a number of common data processing nodes. These nodes allow you to filter data, adding/deleting fields, perform lookups, and use a JavaScript node for more complex transformations before writing the data to MongoDB. This ensures that the data in your materialized view is exactly how you need it.

TapView’s Key Features

Support Major Relational Database Connectors

TapView supports over 10 data sources, making it an excellent solution for enterprises with diverse data architectures. These sources include:

Relational Databases: PostgreSQL, MySQL, Oracle, SQL Server, DB2, SayBase, MariaDB.
NoSQL Databases: MongoDB and MongoDB Atlas.
In-Memory Databases: Redis
Distributed Data Streaming Platforms: Kafka
File Formats: CSV

Real-Time Materialized Views with Multi-Source Integration

TapView is designed to create real-time updated materialized views from multiple relational databases (PostgreSQL, MySQL, Oracle, SQL Server). Unlike traditional views, which only provide static data when queried, materialized views store query results in a physical table, greatly improving read performance. TapView continuously refreshes and updates these views using built-in CDC (Change Data Capture) connectors, ensuring that MongoDB/Atlas remains synchronized with the latest data from the source systems.

What sets TapView apart is its ability to integrate data from multiple databases into a single unified materialized view. This allows you to consolidate data from various sources, such as customer information from multiple databases (PostgreSQL, MySQL, Oracle, DB2), into one cohesive MongoDB collection. This data aggregation simplifies complex workflows and provides real-time access to consolidated data, enabling better decision-making.

Schema Mapping from Relational databases to NoSql Database Migration

TapView offers robust schema mapping capabilities to convert relational database schemas into MongoDB’s flexible document-based model.

Manual Schema Mapping: Users can manually map relational database schemas to MongoDB using Tapview user friendly interface. This includes the ability to define how related tables (one-to-one or one-to-many relationships) should be represented in MongoDB.
Embedded Objects and Arrays: TapView can write related tables or child tables into MongoDB as embedded objects or arrays. For instance:
- One-to-One Relationships: Data from the related table can be embedded as a sub-document in the parent record.
- One-to-Many Relationships: Data from the child table can be written as an array of embedded objects, ensuring MongoDB collections adhere to best practices for denormalized document design.

Built-in Data Processing Nodes for Data Transformation

One of the standout features of TapView is its extensive set of built-in data processing nodes, which enable data transformations before writing to the target MongoDB/Atlas materialized view. These data processing nodes offer capabilities such as adding or removing fields, data cleansing, and complex transformations using custom JavaScript scripts in the JS data processing node. These data processing nodes enable a variety of data transformations, making it easier to manage and manipulate data as it flows from source systems to materialized views in MongoDB.

Low-Coding, User-Friendly Interface

TapView is designed with an intuitive, low-code interface, which makes it easier to set up and manage complex data pipelines. Even without extensive coding knowledge, users can quickly design data flows, set up real-time synchronization, and create materialized views—all with minimal effort. This makes TapView suitable for both end users and data analysts.

MongoDB Relational Migrator (RM)

MongoDB Relational Migrator (RM) is a powerful tool designed for real-time data migration from relational databases to MongoDB, offering capabilities to map relational schemas into MongoDB’s flexible document-based structure.

In addition to migrating data, MongoDB RM also supports basic data transformations. Users can map fields between relational tables and MongoDB documents, modify data types, and add or remove fields during the migration process. These transformations are relatively straightforward but allow users to adapt relational data to MongoDB’s document model more effectively. Monogdb RM Supports below major relational databases.

SQL Server
MySql
PostgreSql
Oracle
Db2 (Preview)
Sybase ASE (Preview)

Key Features of MongoDB RM:

Relational Database Migration:

MongoDB RM specializes in migrating data from relational databases such as MySQL, PostgreSQL, SQL Server, Oracle, and more. It is optimized for real-time data migration from relational database sources to MongoDB.

Schema Mapping:

It provides the ability to map relational database schemas to MongoDB’s flexible document model. Users can define how data from relational tables is translated into MongoDB collections, maintaining the integrity of the data while leveraging MongoDB’s document-based structure.

Basic Data Transformation:

MongoDB RM allows basic data transformations, such as mapping fields from relational tables to MongoDB’s documents, adding or removing fields, and simple data type conversions.

Real Time Data Processing:

MongoDB RM enables real-time synchronization between relational databases and MongoDB using Change Data Capture (CDC). It continuously captures changes from the source relational database and applies them to MongoDB in real time, ensuring data consistency.

TapView Vs MongoDb Relational Migrator(RM) Table

Feautre	TapView	Mongodb RM
Real-Time Data Synchronization	Yes, with continuous updates	Yes, though it is designed to run only for the period of the migration process
Multi-Source Integration	Yes, integrates data from multiple relational databases into one materialized view	No, supports single-source integration (one relational DB at a time)
Data Transformation Capabilities	Extensive, with data filtering, field manipulation, complex transformations via JavaScript nodes	Basic transformations, such as mapping fields, adding/removing fields, and changing data types
Supported Data Sources	10+ including all major relational databases (PostgreSQL, MySQL, Oracle, SQL Server, DB2, SayBase, kafka, MariaDB, Redis), NoSQL.	Supported six Relational databases (MySQL, PostgreSQL, SQL Server, Oracle, DB2, Sybase ASE)
Low-Code Interface	Offers an intuitive, user-friendly low-code interface for designing data flows and real-time synchronization	Provides user-friendly interface, but with fewer advanced options
Data Flow Monitoring	Integrated data flow monitoring with detailed visualizations, graphs, and error tracking	Provides basic monitoring but lacks advanced, detailed flow analytics
Use Case	Building real-time updated materialized views and complex data integration from multiple sources to monogdb with simple and comlex data tranformation	One time data migration from relational databases to MongoDB/Atlas

Summary

Both MongoDB Relational Migrator (RM) and TapView offer real-time data migration and synchronization capabilities, and their suitability depends on your specific business use case.

TapView, is ideal for scenarios where you need to integrate data from multiple sources such as relational databases into a single materialized view. You can also use it for simple RDBMS to MongoDB replication. It supports schema mapping, allowing users to define how relational data should be structured in MongoDB, including embedding related or child tables as objects or arrays for one-to-one and one-to-many relationships. TapView also excels in handling both simple and complex data transformations, making it suitable for advanced integration tasks.
MongoDB RM is a powerful tool for real-time migration of data from relational databases to MongoDB, offering schema mapping and transformation capabilities to align relational schemas with MongoDB’s flexible document model. It is particularly effective for straightforward use cases, such as migrating data from a single database or creating updated materialized views with simple transformations.

The choice between TapView and MongoDB RM ultimately depends on your business needs. For complex data integration from multiple sources with advanced transformation requirements, TapView is an excellent choice. For simpler migration tasks involving one database at a time with basic transformations, MongoDB RM is a great fit.