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Database & Data
NoSQL Database Solutions (MongoDB, DynamoDB)
NoSQL database solutions using MongoDB and DynamoDB. We design and implement document, key-value, and wide-column databases for high-scale, flexible data needs.
Get Started99.9%
Uptime Achieved
10x
Query Speed Gains
Zero
Data Loss
24/7
Support Available
Service Category
NoSQL Engineering
Ideal For
Applications needing flexible schemas, high write throughput, or unlimited horizontal scaling with NoSQL databases.
Timeline
2 – 8 weeks
Why Choose MicrocosmWorks for NoSQL Solutions?
NoSQL databases excel at specific data patterns — flexible schemas, high write throughput, horizontal scaling, and hierarchical data. We help you choose the right NoSQL technology, design optimal data models, and implement solutions that leverage each database's strengths while avoiding common pitfalls.
Our NoSQL Capabilities
- MongoDB Architecture — Design document schemas, implement aggregation pipelines, configure replica sets, and set up sharded clusters for horizontal scaling.
- DynamoDB Design — Create single-table designs, design access patterns, implement GSIs/LSIs, and optimize for consistent performance at any scale.
- Data Modeling — Design document structures that optimize for your read/write patterns — embedding vs referencing, denormalization strategies, and schema evolution.
- Migration from SQL — Migrate from relational databases to NoSQL with proper data transformation, query pattern redesign, and validation.
- Performance Optimization — Optimize read/write patterns, index strategies, hot partition detection, and capacity planning for cost-efficient scaling.
- Multi-Database Architecture — Design systems that combine NoSQL with relational databases — right tool for each data access pattern.
Technology Stack
We work with MongoDB Atlas for managed document storage, AWS DynamoDB for serverless key-value, Redis for caching and sessions, Cassandra for wide-column time-series, and Elasticsearch for search. All implementations include proper monitoring, backup, and disaster recovery.
Who This Is For
Applications with flexible schema requirements, high-write workloads, hierarchical data, or unlimited horizontal scaling needs. Also for teams that chose NoSQL but are struggling with data modeling, performance, or cost optimization. We help you get the most from NoSQL.
Our Process
1
Data Analysis
Analyze access patterns, data relationships, scale requirements, and consistency needs.
2
Database & Model Design
Select database technology, design data models, and plan indexing and partitioning strategies.
3
Implementation
Implement data models, build access layer, configure replication, and set up backups.
4
Performance Testing
Load test with realistic data volumes, optimize hot paths, and validate scaling behavior.
5
Operations Setup
Deploy monitoring, set up alerts, document data models, and establish operational procedures.
Technology Stack
Document
MongoDB AtlasMongoDBDocumentDBCouchDB
Key-Value
DynamoDBRedisMemcachedScyllaDB
Search & Analytics
ElasticsearchOpenSearchClickHouse
Tooling
MongooseDynamooseCompassNoSQL Workbench
Industries We Serve
IoTGamingSocial PlatformsE-CommerceContent PlatformsSaaS
Ready to Implement NoSQL?
Let's design a NoSQL solution that handles your data at any scale with the right technology.
Frequently Asked Questions
MicrocosmWorks specializes in MongoDB, DynamoDB, Cassandra, Redis, and Couchbase. We help you choose the right NoSQL database based on your data model, consistency requirements, and scalability needs.
Our NoSQL database consulting and development services range from $20-$45/hour, depending on the database technology and project complexity involved.
NoSQL databases are ideal when you need flexible schemas, horizontal scalability, high write throughput, or when your data is naturally document-oriented, graph-based, or key-value structured. MicrocosmWorks helps you evaluate whether NoSQL is the right fit for your specific use case.
Yes, we design polyglot persistence architectures that combine multiple NoSQL databases—for example, MongoDB for document storage, Redis for caching, and Neo4j for graph relationships—all integrated into a cohesive data layer.
We implement eventual consistency patterns with conflict resolution strategies, use change data capture for cross-database synchronization, and configure tunable consistency levels in databases like Cassandra to balance performance with data accuracy.