Migrating from Relational Databases

Migration guidelines for relational database users. In this section, we use MySQL as an example relational database.

When migrating from MySQL to Couchbase Server, there are several things that you might want to think about, starting with the data model, data types, and feature set differences.

Data Model – Mapping from MySQL to Couchbase Server

Data modeling for RDBMS has been a well-defined discipline for many years. Professionals, including novice users, have been practicing techniques such as logical to physical mapping and normalization / de-normalization. However, the old-school RDBMS data modeling techniques still play a meaningful role for those who are new to the NoSQL technology.

Table 1. Concept mapping between MySQL and Couchbase Server
MySQL	Couchbase Server
Database	Bucket
Table	Bucket(s)/Keyspaces
Row	Document
Column	Field
Fixed schema	Flexible schema

Table 2. Datatype mapping between MySQL and Couchbase Server
Data type	MySQL	Couchbase Server
Case sensitive	Yes/No	Yes
Numbers	Yes	Yes
String	Yes	Yes
Boolean	Yes (as `tinyint`)	Yes
Date time	Yes	Yes (as a string in JSON)
Spatial data	Yes	Yes
MISSING	No	Yes
NULL	Yes	Yes
Object/Arrays	No	Yes
Blobs	Yes	Yes

Feature Set

Like MySQL, Couchbase Server offers a rich set of features and functionality far beyond those offered in simple key-value stores.

With Couchbase Server, you also get an expressive SQL-like query language and query engine called N1QL, which is combined with a new powerful indexing mechanism – Global Secondary Indexes.

Table 3. Feature differences between MySQL and Couchbase Server
Feature	Key difference
Keys/Indexes	Primary keys on keys of (key, value) pair
SQL statements	The result is set in JSON instead of rows and columns. NEST, UNNEST Operations on datetime fields require datetime functions in N1QL. JSON-induced functions in N1QL: JSON, Object, and array functions. Type and comparison functions. JOIN, sub-query format differences. `USING KEYS` and ON KEYS functions
Explain and metadata	Variation in command and results (JSON).

ETL Tools

You might have a spectrum of relational, operational, and analytical data sources in your environment. You might also need more sophistication applied to a data movement situation, such as more than just simple extract-load. In a case like that, you can use an extract-transform-load (ETL) tool such as talend-connector::index.adoc. With Talend, you can easily move data between Couchbase Server and any other data source.