10 NoSQL databases available as alternatives to MongoDB
Tags: mongodb, database, datascience, dataengineering
Published: 2023-09-08 07:30:53

Here is a list of 10 NoSQL databases as alternatives to MongoDB, along with their respective pros and cons:

1. [**Cassandra**] (http://cassandra.apache.org/)
A highly scalable, distributed NoSQL database designed for handling large volumes of data with high availability and fault tolerance.
   - **Pros**: Excellent horizontal scalability, support for multi-data center replication, and high write throughput.
   - **Cons**: Steeper learning curve, complex data modeling, and eventual consistency can be challenging.

2. [**Couchbase**](https://www.couchbase.com/) 
A distributed, memory-first NoSQL database with built-in caching and support for both key-value and document-based data.
   - **Pros**: High performance, native support for JSON data, and seamless scalability.
   - **Cons**: Limited support for complex queries, and community edition lacks certain features.

3. [**Redis**] (https://redis.io/)
An in-memory data store often used for caching and real-time data processing. It supports various data structures and is known for its speed.
   - **Pros**: Blazing-fast read and write operations, support for complex data types, and rich ecosystem.
   - **Cons**: Limited storage capacity compared to disk-based databases, and data is not persistently stored by default.

4. [**Neo4j**] (https://neo4j.com/)
A graph database designed for efficiently storing and querying graph data, making it ideal for applications with complex relationships.
   - **Pros**: Excellent for handling connected data, supports graph query languages, and provides powerful data modeling capabilities.
   - **Cons**: May not be the best choice for non-graph data, and can be resource-intensive for large-scale graphs.

5. [**CouchDB**](https://couchdb.apache.org/)
A document-oriented NoSQL database known for its distributed architecture, offline support, and easy replication.
   - **Pros**: Highly available, schema-free, and supports flexible data modeling with JSON documents.
   - **Cons**: Query performance can be slower compared to other databases, and complex queries may require map-reduce functions.

6. [**Riak**] (https://riak.com/)
A distributed NoSQL database designed for high availability and fault tolerance, making it suitable for large-scale systems.
   - **Pros**: High availability, easy scalability, and strong consistency options.
   - **Cons**: Limited support for complex queries, and adoption has declined in recent years.

7. [**HBase**](https://hbase.apache.org/)
A distributed and scalable NoSQL database modeled after Google's Bigtable, primarily used for handling massive amounts of sparse data.
   - **Pros**: Scales well horizontally, strong consistency, and integrates with Hadoop for analytics.
   - **Cons**: Requires substantial resources, complex setup, and may not be suitable for small-scale applications.

8. [**Amazon DynamoDB**](https://aws.amazon.com/dynamodb/)
A fully managed NoSQL database service by AWS that offers seamless scalability, high availability, and low latency.
   - **Pros**: Serverless, automated scaling, and integrations with other AWS services.
   - **Cons**: Can be expensive for large workloads, and limited support for complex queries.

9. [**ScyllaDB**]  (https://www.scylladb.com/)
A highly performant, distributed NoSQL database that is compatible with Apache Cassandra but designed for lower latency and higher throughput.
   - **Pros**: Exceptional performance, compatibility with Cassandra, and improved resource utilization.
   - **Cons**: Smaller user base compared to Cassandra, and may require fine-tuning for specific use cases.

10. [**ArangoDB**]  (https://www.arangodb.com/)
A multi-model database that supports document, graph, and key-value data models within a single database engine.
    - **Pros**: Versatile data model support, multi-model querying, and native JavaScript-based queries.
    - **Cons**: Smaller community compared to some other databases, and complex queries can be challenging.

11. [**Hypertable**]  (https://hypertable.org/)
An open-source, distributed NoSQL database inspired by Google's Bigtable, designed for large-scale data storage.
    - **Pros**: Scalability, high write throughput, and efficient data compression.
    - **Cons**: Limited adoption and community support, and less feature-rich compared to some other databases.

12. [**RethinkDB**]  (https://rethinkdb.com/)
A distributed database known for its real-time data support and JSON-like query language.
    - **Pros**: Real-time push architecture, ease of use, and automatic sharding.
    - **Cons**: Project was officially discontinued, so long-term support and community contributions may be limited.

Choosing the right NoSQL database for your company is a critical decision, as it can significantly impact your application's performance, scalability, and development efforts. Here's a checklist of ten considerations to help you make an informed choice:

1. **Data Model Compatibility**:
   - Determine the most suitable data model for your application: document, key-value, column-family, graph, or time-series.
   - Ensure the NoSQL database you choose supports your preferred data model.

2. **Scalability**:
   - Evaluate your scalability requirements. Do you need horizontal scalability to handle growing data and user loads?
   - Choose a NoSQL database that can scale out easily and efficiently.

3. **Consistency Model**:
   - Decide on the desired consistency level for your data: strong consistency, eventual consistency, or something in between.
   - Select a NoSQL database that provides the appropriate consistency guarantees for your use case.

4. **Query Capabilities**:
   - Assess your query needs. Will you require complex queries, aggregations, or full-text search?
   - Ensure the chosen NoSQL database supports the query capabilities you need.

5. **Data Durability**:
   - Determine your data durability requirements. How critical is data loss prevention for your application?
   - Choose a database that offers the desired durability features, including replication and backup options.

6. **Data Distribution**:
   - Consider geographical distribution requirements. Do you need multi-data center or global data distribution?
   - Select a database with built-in support for data replication across regions.

7. **Community and Ecosystem**:
   - Examine the size and activity of the NoSQL database's community.
   - Ensure there is a thriving ecosystem of tools, libraries, and community support.

8. **Operational Overhead**:
   - Evaluate the operational complexity of the database. Is it easy to set up, manage, and monitor?
   - Choose a database that aligns with your team's expertise and available resources.

9. **Data Security and Compliance**:
   - Consider data security and compliance requirements, including encryption, access control, and auditing.
   - Select a database that offers robust security features to meet your industry and regulatory standards.

10. **Cost and Licensing**:
    - Estimate the total cost of ownership, including licensing fees, cloud infrastructure costs, and operational expenses.
    - Ensure the chosen database aligns with your budget constraints and provides a suitable licensing model.

Remember that the choice of a NoSQL database should align closely with your specific use case and business needs. It's often valuable to prototype or perform a proof of concept to validate the database's suitability before making a long-term commitment. Additionally, keep in mind that the database landscape is continually evolving, so periodically reassess your choice to ensure it still meets your company's requirements.