Empower Your Data: Expert Database Development Services by NovaDev

Introduction
What is a Database and What Is Its Purpose?
Database Development Services
Database Consulting
Operational Databases
Analytical Databases
Data Warehouse Software Solutions
Database Optimization
Database Migration
Database Testing
Data Mining
Databases We Work With
- Relational Databases
- NoSQL Databases
- Cloud Databases
- Columnar and Wide Column Databases
- Object-oriented Databases
- Key-value Databases
- Hierarchical Databases
- Document Databases
- Graph Databases
- Time Series Databases
- Microsoft SQL Server: A robust, scalable database management system designed for the enterprise environment.
- Oracle Database: Offers advanced reliability, security, and scalability for all your business needs.
- MySQL: The world’s most popular open-source database, known for its performance and reliability.
- PostgreSQL: An advanced open-source relational database with a strong reputation for reliability, feature robustness, and performance.
- IBM Db2: Offers industry-leading data management and analytics capabilities for enterprise and data-intensive applications.
- Apache Cassandra: A distributed NoSQL database designed for handling large amounts of data across many commodity servers.
- MongoDB: A document database with the scalability and flexibility that you want with the querying and indexing that you need.
- CouchDB: A database that uses JSON for documents, JavaScript for MapReduce queries, and regular HTTP for its API.
- CouchBase: An open-source, distributed, NoSQL document-oriented database optimized for interactive applications.
- Microsoft Azure SQL Database: A fully managed relational cloud database service that offers SQL Server engine compatibility.
- Amazon Relational Database Service (RDS): Makes it easy to set up, operate, and scale a relational database in the cloud.
- Oracle Autonomous Database: A fully automated, self-securing database that includes all Oracle Database features and capabilities.
- Google BigQuery & Azure SQL Data Warehouse: Fast, economical, and fully managed data warehouse services for large-scale data analytics.
- Cassandra & HBase: Wide column stores offering robust support for clusters spanning multiple datacenters, with asynchronous masterless replication.
- MariaDB: An enhanced, drop-in replacement for MySQL, including columnar storage capabilities for scalable, high-performance querying.
- Wakanda: Provides a full stack JavaScript framework including a NoSQL object-oriented database.
- ObjectStore: A pioneer in object-oriented database technology and data persistence solutions.
- Amazon DynamoDB: A key-value and document database that delivers single-digit millisecond performance at any scale.
- Redis: An open-source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker.
- IBM Information Management System (IMS): A premier transaction and hierarchical database management system.
- Windows Registry: A hierarchical database that stores low-level settings for the Microsoft Windows operating system and for applications that opt to use the registry.
- MongoDB & Amazon DocumentDB: Offer flexibility in storing, processing, and querying data as JSON-like documents.
- Apache CouchDB: Designed for ease of use and having a scalable architecture.
- Datastax Enterprise Graph: Built on the best distribution of Apache Cassandra, DataStax Enterprise is the always-on, scalable data platform for cloud applications.
- Neo4J: A graph database management system described as an ACID-compliant transactional database with native graph storage and processing.
- Druid: Designed for workflows where fast queries and ingest really matter.
- eXtremeDB & InfluxDB: Optimized for time series data, enabling high-performance data ingestion and real-time analytics.
Our Development Process
Requirements Gathering
Identifying the specific needs and goals of your project to ensure the database solution aligns with your business objectives.
Conceptual Design
Outlining the high-level structure and relationships within the database to represent business information in a database model.
Normalization
Applying normalization rules to reduce data redundancy and improve data integrity within the database.
Data Modeling
Creating detailed models for how data is stored, accessed, and managed, including entity relationships and data flow.
Schema Design
Defining the logical structure of the database schema, including tables, columns, data types, and constraints to ensure data consistency and support application requirements.
Development
Implementing the database design using the selected database management system, following best practices for security, performance, and scalability.
Data Enrichment
Enhancing the database with external data sources or computed metrics to increase the value and usability of the data.
Testing and Optimization
Conducting thorough testing to identify and fix issues related to functionality, performance, security, and integrity of the database system. Optimizing queries and configurations for improved performance.
Documentation
Creating comprehensive documentation of the database design, configurations, and operational procedures to support maintenance and future development.
Deployment
Rolling out the database system into a production environment, ensuring it is properly configured and optimized for real-world use.
Monitoring and Optimization
Continuously monitoring the database performance and health, making adjustments as needed to handle new requirements or to improve efficiency and performance.
Benefits
