KEY TAKEAWAYChoosing the right MongoDB alternative in 2025 depends on your workload shape, latency targets, and operational model; here are the top 7 options and when to use each:
- Apache Cassandra: Scalable, multi-region, high-throughput NoSQL for global writes.
- Redis: In-memory speed for real-time caching, queues, and analytics.
- Amazon DynamoDB: Serverless key-value store with auto-scaling and reliability.
- OrientDB: Graph-focused, multi-model database for complex relationships.
- CouchDB: Offline-first document store for distributed web/mobile apps.
- ArangoDB: Multi-model database unifying documents, graphs, and key-value.
- RethinkDB: Real-time JSON database for live updates and dashboards.
With organizations generating huge volumes of Unstructured Data, the need for NoSQL Databases is on the rise. Relational Databases organize data into tables or relations, which are intersections of rows and columns. This makes them limited to storing Structured Data only. NoSQL databases emerged in 2009 to overcome this limitation. They can be used in massive data applications to store Unstructured Data.
MongoDB is a popular NoSQL database management system. It is an open-source NoSQL database that uses the document-oriented database model. MongoDB groups data into documents and collections rather than tables, hence, it can be used to store different types of data. It is well-known for offering high performance, easy scalability, and high availability.
However, data consumption in MongoDB is high as a result of denormalization. Developers have also reported different issues with MongoDB, hence, they are leaving the Database Management System. In this article, we have prepared a list of the top MongoDB Alternatives for you to use.
Table of Contents
What is MongoDB?
MongoDB is a well-known Open-Source NoSQL Database written in C++. MongoDB is a Document-oriented Database that uses JSON-like documents with a Dynamic Schema to store data. It means that you can store your records without having to worry about the Data Structure, the number of fields or the types of fields used to store values. Documents in MongoDB are similar to JSON objects.
You can change the structure of records (which MongoDB refers to as Documents) by simply adding new fields or deleting existing ones. This feature of MongoDB allows you to easily represent Hierarchical Relationships, Store Arrays, and other complex Data Structures. Nowadays, many tech giants, including Facebook, eBay, Adobe, and Google, use MongoDB to store their large amounts of data.
Hevo Data is a no-code data pipeline platform that helps load data from various sources, like MongoDB, to your desired destinations. With 150+ pre-built integrations, Hevo makes connections and data transformation fast and easy.
Hevo offers:
- Minimal Learning: Hevo’s simple and interactive UI makes it extremely simple for new customers to work on and perform operations.
- Live Support: The Hevo team is available 24/7 to extend exceptional support to its customers through chat, E-Mail, and support calls.
- Transformational Capabilities: It provides pre- and post-load transformational capabilities to ensure your data is always analysis-ready.
- Transparent Pricing: Hevo offers transparent pricing with no hidden fees, allowing you to budget effectively while scaling your data integration needs.
Try Hevo today to experience seamless data transformation and migration.
Get Started with Hevo for FreeBest MongoDB Alternatives
The following are the top MongoDB Alternatives that you should consider:
1. Apache Cassandra
Apache Cassandra is an open-source NoSQL database built for organizations that need high availability, scalability, and fault tolerance without compromising on performance. Originally developed at Facebook, it has since become a preferred choice for distributed, large-scale systems handling massive data volumes.
Cassandra uses a peer-to-peer architecture where every node in the cluster operates independently, removing single points of failure. This makes it ideal for applications that demand always-on uptime and quick horizontal scalability.
Its ability to replicate data seamlessly across multiple data centers and cloud zones ensures operational continuity and minimal downtime.
Key Features
- Peer-to-Peer Architecture: Eliminates bottlenecks and single points of failure.
- Linear Scalability: Add new nodes without downtime to handle growing workloads.
- Multi-Data Center Replication: Ensures fault tolerance and data durability across regions.
- Tunable Consistency: Adjust read/write consistency levels based on application needs.
- High Write Throughput: Optimized for write-heavy workloads and massive ingestion rates.
Why It’s a Better Alternative to MongoDB
- Ideal for real-time, high-throughput workloads such as IoT, financial systems, or telecom data platforms.
- Offers superior scalability for large, distributed datasets across multiple nodes.
- Zero single point of failure, unlike MongoDB’s primary–secondary architecture.
- More resilient and fault-tolerant in multi-region or hybrid cloud setups.
2. Redis
Redis is an open-source, in-memory data store designed for extreme speed and simplicity. It supports a variety of data structures, making it suitable for caching, session management, and real-time analytics.
Redis can be deployed using Active-Active or Active-Passive replication architectures, ensuring data availability and minimal downtime.
With sub-millisecond response times and efficient memory usage, Redis is a popular choice for performance-critical applications.
Key Features
- In-memory storage for ultra-fast performance
- Supports multiple data structures (Lists, Hashes, Sets, Strings, etc.)
- Active-Active replication for high availability
- Built-in search and caching capabilities
- Linearly scalable architecture for growing workloads
Why It’s a Better Alternative to MongoDB
- Easier to deploy for small-scale, low-latency applications
- Far faster for in-memory operations and caching use cases
- Simpler and lighter for applications needing high-speed reads/writes
- Offers real-time data processing with minimal latency
3. DynamoDB
DynamoDB is a fully managed NoSQL database service from AWS, designed for seamless scalability and consistent single-digit millisecond performance.
It supports both key-value and document data models, making it versatile for a wide range of applications from gaming to IoT.
DynamoDB also offers built-in backup, restore, and in-memory caching (DAX), reducing operational overhead while ensuring enterprise-grade reliability.
Key Features
- Fully managed and serverless architecture
- Multi-region, multi-master replication
- Automatic scaling with no downtime
- Integrated in-memory caching (DAX)
- Predictable performance at any scale
Why It’s a Better Alternative to MongoDB?
- Ideal for enterprises running global-scale applications on AWS
- No maintenance burden — AWS handles scaling, patching, and uptime
- Global scalability with multi-region replication built in
- Consistent millisecond response time at any workload size
4. OrientDB
OrientDB is an open-source, multi-model database that combines the power of graph, document, key-value, and object models in one system.
It’s ideal for applications that require graph-based relationships, such as recommendation engines, fraud detection, and knowledge graphs.
Its integrated graph engine eliminates the need for multiple systems, simplifying data management and architecture.
Key Features
- Multi-model support (Graph, Document, Key-Value, Object)
- True Graph Engine for complex relationship modeling
- Free clustering and high availability
- SQL-like query language for ease of use
- Built-in support for ACID transactions
Why It’s a Better Alternative to MongoDB
- Better suited for relationship-heavy data models
- Handles graph-based data natively, unlike MongoDB
- Combines multiple models in one engine for flexibility
- Offers built-in clustering for free, reducing infrastructure cost
5. CouchDB
CouchDB is an open-source, document-oriented NoSQL database that stores data in JSON format.
It’s built for web-scale applications handling loosely structured data, with powerful synchronization and replication capabilities across distributed environments.
Its RESTful HTTP API makes integration simple and developer-friendly, ideal for modern web apps.
Key Features
- Document-oriented storage using JSON
- HTTP/REST-based API for easy access
- Multi-master replication for distributed systems
- Incremental replication and synchronization
- Session-based authentication and data durability
Why It’s a Better Alternative to MongoDB?
- Ideal for web-scale apps managing semi-structured data
- Easier integration with web and mobile applications via REST API
- Superior replication and offline sync for distributed environments
- Lightweight setup and fully open-source
6. ArangoDB
ArangoDB is a native multi-model database that supports graph, document, and key-value data models using a unified query language.
It’s optimized for performance and flexibility, enabling complex data relationships without managing multiple systems.
ArangoDB also includes a built-in search engine and a microservices framework, making it a strong fit for modern, distributed applications.
Key Features
- Multi-model (Graph, Document, Key-Value) support
- AQL — a SQL-like query language
- Integrated search and microservices capabilities
- High availability with cluster setup
- Large and active open-source community
Why It’s a Better Alternative to MongoDB
- Highly extensible for analytical and high-performance workloads
- Unifies multiple data models under one system
- Provides native graph and search capabilities MongoDB lacks
- Reduces need for multiple database technologies
7. RethinkDB
RethinkDB can prove to be one of the best MongoDB alternatives for you if your goal is to develop real-time apps. However, you will not receive regular updates as the company was shut down in 2016. RethinkDB is a free and open-source database management system.
Key Features
- Real-time changefeeds for live updates
- Horizontal scalability across data centers
- JSON document storage
- Simple query syntax similar to SQL
- Easy scaling across multiple servers
Why It’s a Better Alternative to MongoDB?
- Completely open-source with no licensing fees
- Native real-time data push to applications (no polling needed)
- Ideal for live dashboards, chats, and collaboration tools
- Simple scaling for distributed environments
Factors to Consider When Choosing a MongoDB Alternative
When selecting a MongoDB alternative, consider the following factors:
- Community Support and Documentation: A strong community and extensive documentation simplify implementation and troubleshooting. Databases like Redis and Cassandra are well-supported, making them easier to adopt.
- Scalability: Evaluate how well the database can handle growing data volumes and user traffic. Some options like Apache Cassandra and DynamoDB, excel in distributed scalability across multiple regions.
- Performance: Analyze the database’s speed for read/write operations, latency, and consistency. Redis offers high performance with in-memory data storage, making it ideal for real-time applications.
- Data Model: Choose a database that fits your data structure needs. For example, ArangoDB supports multiple models like graphs and documents, while DynamoDB focuses on key-value pairs.
- Licensing and Pricing: Assess the cost-effectiveness of the database, considering free tiers, customization options, or subscription plans. Open-source databases like CouchDB and OrientDB are budget-friendly, while DynamoDB uses a pay-as-you-go model.
Conclusion
NoSQL Databases are ideal for storing unstructured data as they don’t organize data into relations, unlike traditional relational databases. MongoDB, a popular NoSQL Database, follows a document-oriented model that groups data into documents and collections. However, MongoDB’s denormalization approach often results in high data consumption, making it worthwhile to explore alternatives like Redis, Apache Cassandra, RethinkDB, DynamoDB, OrientDB, CouchDB, and ArangoDB.
As your business grows, data generation surges across SaaS apps and databases. Managing it requires integration, cleaning, and loading into a Cloud Data Warehouse. Hevo Data simplifies this process, saving time and resources while ensuring seamless data management. Sign up for Hevo’s 14-day free trial and experience seamless data migration.
FAQs
Why look beyond MongoDB in 2025?
As data volume and diversity grow, teams need engines optimized for specific access patterns (e.g., write-heavy time series, in-memory latency, or native graph). Some alternatives reduce operational overhead or improve multi-region behavior. Others provide serverless scale or multi-model flexibility that simplifies architecture. Picking a fit-for-purpose store often lowers cost and complexity over time.
Which MongoDB alternative is best for global, write-heavy workloads?
Apache Cassandra and DynamoDB are top picks. Cassandra offers linear scalability and tunable consistency across regions when you manage clusters yourself. DynamoDB provides serverless autoscaling and global tables for simplified operations. Your choice hinges on control needs, pricing model, and AWS lock-in tolerance
What if ultra-low latency is my top priority?
Choose Redis when you need sub-millisecond responses for hot paths, queues, rate limiting, or session/state stores. It supports rich data types and Active-Active topologies. For durability beyond RAM, consider Redis persistence or Redis Enterprise options. Pair with a colder store if you also need large, historical analytics.
When should I prefer a graph database over MongoDB?
If your questions are about relationships—shortest paths, recommendations, fraud rings-graph stores like OrientDB (or ArangoDB’s graph model) deliver native traversals and simpler query logic. You’ll avoid complex joins or application-level graph logic. This usually results in faster queries and clearer schemas for highly connected data.
Share it with your connections.
-
Share To LinkedIn
-
Share To Facebook
-
Share To X
-
Copy Link
