Choosing the correct database management system can significantly affect the performance of your application. With a wide array of options available, you should evaluate the unique requirements of your project before making a decision. Both relational and NoSQL databases offer distinct advantages, tailored to specific use cases.
Two popular choices in this context are CockroachDB, a relational database, and MongoDB, a NoSQL document-oriented database. This article will outline CockroachDB Vs MongoDB differences to guide you in selecting the right one.
CockroachDB Overview
CockroachDB is a robust cloud-native distributed SQL database that offers a scalable solution for managing data. Built on a transactional and strongly consistent key-value store, it lets you handle large volumes of data across multiple servers without losing consistency.
One of the key attributes of CockroachDB is its resilience. Data is automatically replicated across various nodes, ensuring that even if a server fails, your data remains accessible. This helps the system remain resilient and operational and minimizes disruptions during hardware failures or maintenance.
Key Features of CockroachDB
Here are some of the key features of CockroachDB:
- Automatic Rebalancing: CockroachDB automatically rebalances your data across nodes to optimize performance and ensure even load distribution without manual intervention.
- Geo-Partitioning: You can geo-partition your data to keep specific data closer to where it’s most needed, improving performance for region-specific users while still maintaining global consistency.
- Online Schema Changes: CockroachDB enables you to make schema changes without downtime. You can alter tables and indexes on the fly without disrupting your application’s availability.
MongoDB Overview
MongoDB is a document-oriented, non-relational database management system that provides a dynamic schema for storing data. Instead of utilizing tables with rows and columns like traditional SQL databases, MongoDB lets you store data in a flexible, JSON-like format called BSON (Binary JSON).
As a NoSQL database, MongoDB enables you to handle structured or unstructured data with ease. Each record in a MongoDB database is a document, which can contain nested fields, arrays, and even other documents. This flexibility lets you model your data in a way that reflects the real-world entities and relationships in your application.
Key Features of MongoDB
Here are some of the key features of MongoDB:
- Ad-hoc Queries: MongoDB supports ad hoc queries, enabling you to perform dynamic queries without predefined schema definitions. This facilitates exploration and analysis of data without rigid structures.
- Unified Query API: MongoDB’s unified query API lets you effortlessly work with any data type, including time series, arrays, and geospatial data. The API provides a single interface for operational, analytical, and search workloads.
- Time to Live (TTL) Indexes: TTL Indexes in MongoDB are specialized single-field indexes that automatically remove documents from a collection after a specific time period. This feature is especially useful for managing data that only needs to be retained temporarily, such as logs or session information.
CockroachDB Vs MongoDB
According to a study, 24.8% and 1% of developers use MongoDB and CockroachDB, respectively. However, both databases offer unique features tailored to different use cases. In this section, Let's explore the key differences between CockroachDB vs MongoDB in detail.
Data Model
CockroachDB follows a relational data model, similar to traditional SQL databases. Data is organized into tables, each defined by a fixed schema that specifies the data types (attributes) stored in each column. Each column allows values of data of a single data type. You can further enforce referential integrity across the database through column-level constraints such as primary and foreign keys. Therefore, whenever values are modified, constraints are checked, and changes that violate the constraints are rejected, ensuring data integrity.
In contrast, MongoDB uses a document-based data model, which offers much more flexibility. Data is stored as JSON-like documents, and unlike relational databases, collections in MongoDB don’t require a rigid schema. Each document in a collection can have a different set of fields, and the data types for those fields can vary between documents. If you want to enforce some structure, MongoDB allows you to set schema validation rules, but these are optional.
Indexes
An index is a logical object that greatly improves the query performance. In CockroachDB, a primary index is automatically created on the primary key of each table. While this index is useful for filtering based on the primary key, it won’t help when searching through other columns.
However, you can also create secondary indexes to query on non-primary key columns. In addition to explicitly defined indexes, CockroachDB automatically creates secondary indexes for columns with the UNIQUE constraint. Besides, tables are not locked while creating indexes due to CockroachDB support for online schema changes.
In MongoDB, if your application frequently queries the same fields, you can create indexes on those fields to speed up performance. By default, MongoDB automatically creates a unique index on the _id field while creating a collection. This index prevents you from adding two documents with the same value for the _id field.
MongoDB also supports multiple secondary indexes that you can define on any field in the document, such as compound, array, and geospatial indexes. However, MongoDB has some limitations; for instance, it restricts the total number of indexes per collection to 64.
Transactional Consistency
CockroachDB supports distributed transactions and guarantees ACID compliance. By default, it implements serializable isolation, the highest level of transactional integrity, ensuring all operations are completed in a reliable and consistent order. Besides, to avoid conflicts between write and read transactions, CockroachDB uses a timestamp cache that remembers the last read data by an active transaction. This way, you always see serializable consistency, even while running multiple transactions at the same time.
On the other hand, MongoDB introduced multi-document ACID transactions in version 4.0. However, due to limitations in transaction runtime, it's ideal for handling lightweight transactions within single documents. By default, MongoDB automatically aborts any multi-document transaction that runs for more than 60 seconds. Furthermore, the default isolation level in MongoDB is read uncommitted. This allows a transaction to read data that other transactions have modified but not yet committed, potentially leading to issues such as dirty reads.
Multi-Region Capabilities
CockroachDB is natively built to handle multi-region workloads with ease. Every node in a CockroachDB cluster can accept both reads and writes, even if the nodes are spread across different geographic regions. This setup allows for low-latency access to data, as you can interact with the database from the closest node. CockroachDB automatically handles the complexity of replicating and distributing data across regions, ensuring high availability and fault tolerance in case of node or regional failures.
In contrast, MongoDB doesn't offer built-in support for multi-region deployment. While it can be configured for multi-region setups, this often requires complex configurations. Additionally, write operations in MongoDB are typically restricted to a primary node, which can add latency in multi-region setups. MongoDB's Global Clusters feature in MongoDB Atlas allows you to deploy a single database across multiple geographical locations but with more manual configuration compared to CockroachDB.
Replication
CockroachDB uses synchronous replication to ensure data consistency across nodes. It follows a Raft consensus protocol, where data is automatically replicated across multiple nodes or regions to provide fault tolerance and high availability. Each piece of data is replicated to a configurable number of nodes (typically three by default). For a write operation to be successful, the majority of the nodes containing replicas must acknowledge the write. This approach reduces the risk of data loss, as it guarantees that even if one node fails, others still retain the most recent state of the data.
MongoDB, on the other hand, uses an asynchronous replication model for data redundancy and high availability. When a write occurs on the primary node of a replica set, it acknowledges the operation immediately without waiting for secondary nodes to confirm. The primary logs the operation in its operation log (oplog), while secondary nodes asynchronously pull these changes from the oplog and apply them to their data sets.
Although this method provides high throughput and low latency in write operations, it might result in replication lag. While a small delay might be manageable, significant lag can lead to issues, including cache pressure on the primary.
Factors to Consider When Choosing CockroachDB Vs MongoDB
Here is a breakdown of a few essential factors to consider while comparing MongoDB vs CockroachDB:
Data Structure
Choose CockroachDB if you prefer a traditional table-based structure and need strong relationships between data entities. Its relational model is ideal for scenarios requiring complex joins and data integrity. In contrast, opt for MongoDB if you need flexibility in data storage. Its document-oriented approach enables you to store data in various formats, including nested structures and arrays, without predefined schemas.
Query Language
Choose CockroachDB if you are familiar with SQL and want to leverage its capabilities for complex queries. Its support for SQL makes it easier to integrate with existing tools and frameworks. On the flip side, MongoDB is better suited if you prefer working with a NoSQL query language or if your queries primarily focus on document retrieval rather than complex joins.
Cost Considerations
Both MongoDB and CockroachDB offer free versions, but MongoDB’s managed services, such as MongoDB Atlas, can be more cost-effective for basic setups. CockroachDB, on the other hand, tends to be more expensive in managed environments due to its focus on consistency and global distribution. However, if you need reliable, globally distributed data management, CockroachDB might be worth the higher price.
Use Case
If your application needs to operate smoothly across multiple regions, CockroachDB is the better choice due to its built-in multi-region capabilities. It allows all nodes to handle reads and writes regardless of location. While MongoDB can also support multiple regions deployment, you’ll need to spend more time configuring it to achieve consistent performance across regions.
Streamline Data Integration into CockroachDB or MongoDB with Airbyte
By now, you've gained a clear understanding of the key aspects that differentiate CockroachDB vs MongoDB performance. However, regardless of the database you choose, it is crucial to consolidate all your data from required sources, such as CRMs, social media platforms, etc, into your desired database. This helps you gain a unified view of your data, facilitating better analysis and decision-making. To simplify this process, you can utilize data integration tools like Airbyte.
Airbyte is a cloud-based data movement platform that enables you to migrate data from diverse sources to your preferred destination. It offers an extensive catalog of over 400+ pre-built connectors that let you bring data from vast sources to a centralized target system without extensive coding. If you're using CockroachDB or MongoDB and wish to load data from CockroachDB to MongoDB or vice versa, you can easily sync your databases using Airbyte's user-friendly interface.
Below are some of the key features of Airbyte:
- Custom Connectors: You can also utilize Airbyte’s Connector Development Kit (CDK) to build a custom connector in just 30 minutes. This enables you to effortlessly integrate any data source to the destination of your choice.
- RAG Transformations: With Airbyte, you can utilize LLM frameworks, including LangChain or LlamaIndex, to perform complex RAG transformations, such as chunking and indexing. This enables you to simplify the development of LLM applications.
- Change Data Capture (CDC): Airbyte’s CDC feature lets you capture the incremental changes made to the source dataset and replicate them into the destination, maintaining data consistency.
Wrapping Up
This article offered a detailed comparison of CockroachDB Vs MongoDB. However, the decision to choose between CockroachDB and MongoDB depends on your specific application needs, data structure, and performance requirements.
If your priority is data consistency, strong support for transactions, and a more traditional database setup, CockroachDB might be the better choice. On the flip side, if you need high flexibility, scalability, and the capability to handle unstructured data, MongoDB could be a better fit.