Quesma provides a database gateway that translates queries, enabling seamless integration between applications and modern database platforms without the need for query refactoring during migrations. This solution allows businesses to migrate databases safely and efficiently while maintaining backward compatibility with existing applications, reducing costs and deployment time.
Funding
$4.9M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
IVFounders
Product
Problem
Migrating databases can be a complex and costly process, often requiring extensive query refactoring to maintain application compatibility. Businesses face challenges in adopting modern database platforms without disrupting existing systems and incurring significant development overhead.
Solution
Quesma offers a programmable database gateway that acts as a translation layer between applications and modern database platforms, streamlining query integration. By translating queries, Quesma enables safe, step-by-step database migrations without requiring alterations to the application stack or rewriting database query code. This approach preserves backward compatibility, reduces migration risks, and minimizes deployment time, allowing businesses to optimize their investment in modern database technologies. Quesma deploys quickly via Docker or Kubernetes and provides virtually unlimited horizontal scalability.
Target Audience
Quesma targets enterprises seeking to modernize their database infrastructure, optimize costs associated with the Elastic stack (ELK), and development teams aiming to streamline database integrations.
Features
- Query translation enabling seamless integration with modern database platforms
- Compatibility with Kibana/OpenSearch Dashboards to ClickHouse
- Easy deployment via Docker container or Kubernetes operator
- Horizontal scalability to support large environments
- Embedded AI optimizes translation between Elastic and SQL languages, improving query performance
- Automatic schema creation based on data, eliminating manual configuration
- Low overhead due to GoLang implementation, minimizing resource usage and latency
- Support for raw search with skip indexes
- Column-based storage with tailored compression