NoSQL Database Development for Scalable Applications
Implement scalable, flexible, distributed NoSQL databases to handle high-throughput workloads.
👋 Talk to a NoSQL expert.
Trusted and top rated tech team
Distributed database architecture for horizontal scaling
Relational databases struggle to scale when vertical upgrades can’t manage heavy writes, and rigid schemas slow development. NoSQL systems distribute data across nodes with flexible schemas and eventual consistency, supporting high-throughput applications. We collaborate with CTOs facing data growth challenges, where traditional databases create bottlenecks, but fully abandoning relational patterns risks consistency issues.
Our capabilities include:
- Document store implementation
- Key-value store architecture
- Graph database development
- Horizontal scaling and sharding
- Polyglot persistence strategy
- SQL to NoSQL migration
Who we support
We work with organizations where relational databases can’t scale horizontally to meet write-heavy workloads and flexible schema requirements that evolve faster than migration cycles allow.
Startups With Rapid Schema Changes
Your product requirements change weekly and SQL migrations block feature releases. Rigid table structures force architectural decisions before you've validated product-market fit, and altering schemas impacts production.
SaaS Platforms Scaling Write Operations
Your application handles millions of writes daily and vertical database scaling hits cost and performance limits. Read replicas help queries but write bottlenecks remain, and sharding relational databases is complex.
Enterprise Companies With Diverse Data
You manage user sessions, product catalogs, social graphs, and time-series data that don't fit relational models naturally. Forcing everything into SQL creates performance issues and overly complex schemas.
Ways to engage
We offer a wide range of engagement models to meet our clients’ needs. From hourly consultation to fully managed solutions, our engagement models are designed to be flexible and customizable.
Staff Augmentation
Get access to on-demand product and engineering team talent that gives your company the flexibility to scale up and down as business needs ebb and flow.
Retainer Services
Retainers are perfect for companies that have a fully built product in maintenance mode. We'll give you peace of mind by keeping your software running, secure, and up to date.
Project Engagement
Project-based contracts that can range from small-scale audit and strategy sessions to more intricate replatforming or build from scratch initiatives.
We'll spec out a custom engagement model for you
Invested in creating success and defining new standards
At Curotec, we do more than deliver cutting-edge solutions — we build lasting partnerships. It’s the trust and collaboration we foster with our clients that make CEOs, CTOs, and CMOs consistently choose Curotec as their go-to partner.
Why choose Curotec for NoSQL development?
NoSQL adoption fails when teams overlook consistency tradeoffs or use the wrong database for the job. Our engineers know when to use eventual consistency versus strong consistency, which data model suits specific access patterns, and how to implement polyglot persistence without chaos. We ensure the right database choice for each workload instead of forcing one type everywhere.
1
Extraordinary people, exceptional outcomes
Our outstanding team represents our greatest asset. With business acumen, we translate objectives into solutions. Intellectual agility drives efficient software development problem-solving. Superior communication ensures seamless teamwork integration.
2
Deep technical expertise
We don’t claim to be experts in every framework and language. Instead, we focus on the tech ecosystems in which we excel, selecting engagements that align with our competencies for optimal results. Moreover, we offer pre-developed components and scaffolding to save you time and money.
3
Balancing innovation with practicality
We stay ahead of industry trends and innovations, avoiding the hype of every new technology fad. Focusing on innovations with real commercial potential, we guide you through the ever-changing tech landscape, helping you embrace proven technologies and cutting-edge advancements.
4
Flexibility in our approach
We offer a range of flexible working arrangements to meet your specific needs. Whether you prefer our end-to-end project delivery, embedding our experts within your teams, or consulting and retainer options, we have a solution designed to suit you.
NoSQL database implementation capabilities
Document Database Architecture
Key-Value Store Implementation
Graph Database Design
Horizontal Sharding Strategy
Replication & Consistency
Polyglot Persistence Architecture
Technologies we use for NoSQL databases
Document Databases
Our engineers use document stores to manage JSON data with flexible schemas and complex structures for application backends.
- MongoDB — Document store with flexible schema, ACID transactions, aggregation framework, and sharding for horizontal scaling across clusters
- Couchbase — Distributed document system with built-in caching, full-text search, mobile sync, and SQL-like N1QL query language
- Amazon DynamoDB — Managed NoSQL service with automatic scaling, single-digit millisecond latency, and integration across AWS ecosystem
- Azure Cosmos DB — Multi-model platform supporting document, key-value, graph, and column-family with global distribution and consistency options
- CouchDB — Document system with HTTP API, master-master replication, and offline-first architecture for mobile and web applications
- Firebase Firestore — Real-time document store with automatic synchronization, offline support, and mobile SDK integration for app development
Key-Value Stores
Key-value databases provide in-memory caching and session storage with sub-millisecond latency for high-throughput read operations.
- Redis — In-memory data store with sub-millisecond latency, pub/sub messaging, sorted sets, and persistence options for caching and session management
- Memcached — Distributed memory caching system with simple key-value operations, LRU eviction, and high-performance read operations for web applications
- Amazon DynamoDB — Managed key-value service with automatic scaling, single-digit millisecond performance, and seamless AWS service integration
- Riak KV — Distributed key-value database with masterless architecture, eventual consistency, and fault tolerance for high-availability requirements
- Aerospike — High-performance key-value store with flash-optimized storage, real-time processing, and predictable sub-millisecond latency at scale
- Hazelcast — In-memory data grid providing distributed caching, computing, and messaging with Java-based clustering and replication
Graph Databases
Curotec designs graph structures for efficient traversal queries in connected data and recommendation systems.
- Neo4j — Graph store with Cypher query language, ACID transactions, and pattern matching for analyzing relationships and network structures
- Amazon Neptune — Managed graph service supporting property graphs and RDF with Gremlin and SPARQL query languages for AWS deployments
- ArangoDB — Multi-model platform combining graph, document, and key-value with AQL query language for flexible data modeling
- JanusGraph — Distributed graph system optimized for storing and querying billions of vertices and edges across multiple storage backends
- OrientDB — Multi-model platform with graph capabilities, SQL-like queries, and ACID transactions for complex relationship management
- TigerGraph — Native parallel graph engine with real-time analytics, pattern matching, and machine learning integration for large-scale processing
Wide-Column Stores
Wide-column databases process time-series and analytics data using column storage optimized for specific queries.
- Apache Cassandra — Distributed wide-column store with linear scalability, masterless architecture, and tunable consistency for high-availability applications
- Apache HBase — Hadoop-based wide-column store with random real-time read/write access to billions of rows for big data analytics
- Google Cloud Bigtable — Managed wide-column service with petabyte-scale storage, low-latency access, and integration with Google Cloud analytics tools
- ScyllaDB — High-performance Cassandra-compatible system with C++ implementation delivering lower latencies and higher throughput per node
- Amazon Keyspaces — Managed Cassandra-compatible service with automatic scaling, encryption, and backup integrated across AWS infrastructure
- Azure Cosmos DB — Multi-model service supporting column-family access patterns with global distribution and multiple consistency levels
Database Management Tools
Our developers use platforms to monitor cluster health, query performance, and replication across distributed nodes.
- MongoDB Compass — Visual GUI for exploring collections, analyzing queries, building aggregation pipelines, and monitoring performance metrics
- Redis Commander — Web-based management interface for inspecting keys, monitoring memory usage, and executing commands across Redis instances
- Neo4j Browser — Interactive query tool with graph visualization, Cypher editor, and result rendering for exploring relationship structures
- DataStax Studio — Notebook-based tool for Cassandra development with CQL execution, query profiling, and visual schema exploration
- Prometheus & Grafana — Monitoring stack collecting metrics from NoSQL clusters with visualization dashboards and alerting for performance and availability
- Datadog — Cloud monitoring platform with pre-built integrations for NoSQL systems tracking queries, latency, and cluster health
Migration & Integration Tools
Migration frameworks and integration middleware move data from relational databases and connect NoSQL to existing infrastructure.
- Apache Kafka — Streaming platform for moving data between SQL and NoSQL systems with reliable message delivery and event sourcing capabilities
- Debezium — Change data capture tool streaming changes from relational sources to NoSQL targets for real-time synchronization
- Talend — Data integration platform with connectors for migrating and synchronizing data across SQL, NoSQL, and cloud storage systems
- Apache NiFi — Data flow automation tool routing and transforming data between heterogeneous systems with visual pipeline design
- mongorestore & mongodump — Native MongoDB utilities for backup, restore, and migration operations with BSON format support
- AWS Database Migration Service — Managed migration tool moving data to AWS with minimal downtime supporting heterogeneous migrations to DynamoDB
FAQs about our NoSQL database development
How do we choose between SQL and NoSQL?
Use SQL for transactions requiring ACID guarantees and complex joins. Choose NoSQL for high-volume writes, flexible schemas, or horizontal scaling requirements. Most organizations use both strategically based on workload characteristics.
What are the consistency tradeoffs with NoSQL?
Many NoSQL databases use eventual consistency, where reads may return stale data briefly after writes. This trades strict consistency for availability and partition tolerance. Some NoSQL systems offer tunable consistency or ACID transactions for critical operations.
Can we migrate from SQL to NoSQL incrementally?
Yes, polyglot persistence lets you migrate specific workloads while keeping transactional data in SQL. We typically start with read-heavy or schema-flexible workloads, validating performance before migrating additional components.
How do NoSQL databases handle backups?
NoSQL systems use snapshot backups, continuous replication, and point-in-time recovery depending on the database. Distributed architectures provide fault tolerance, but backup strategies must account for eventual consistency during restoration.
How quickly can your engineers start contributing?
Our NoSQL engineers typically begin implementation within the first week. They’re familiar with data modeling patterns, consistency tradeoffs, and operational practices that match distributed database standards.
What operational complexity does NoSQL add?
NoSQL requires monitoring distributed clusters, managing replication lag, and understanding consistency models. We implement monitoring, automate operations, and document runbooks that prepare your team for production management.
Ready to have a conversation?
We’re here to discuss how we can partner, sharing our knowledge and experience for your product development needs. Get started driving your business forward.
