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

1. Cassandra
   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
   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
   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
   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
   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
   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
   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
   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
   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
    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
    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
    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.