Provides a software-defined cloud storage platform that optimizes the performance and efficiency of cloud databases by utilizing a shared-compute architecture. It reduces costs through resource pooling and data reduction, while enabling up to 10x performance improvements, automated data lifecycle management, and zero RPO recovery across multiple cloud environments.
Funding
$30M 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.
TCFounders
Product
Problem
Cloud databases often suffer from performance bottlenecks and inefficiencies due to limitations in underlying storage infrastructure. Traditional cloud storage solutions can lead to over-provisioning, increased costs, and complex data lifecycle management, hindering optimal database performance.
Solution
Silk provides a software-defined cloud storage platform that sits between cloud infrastructure and databases, optimizing performance and efficiency. By utilizing a shared-compute architecture, Silk enables databases to achieve up to 10x performance improvements while reducing costs through data reduction and resource pooling. The platform supports automated data lifecycle management, allowing for streamlined ETL processes and accelerated development agility with Dev/Test environments. Silk also ensures maximum data durability with active-active architecture and self-healing technology, supporting HA and DR across zones, regions, and clouds, with snapshots for rapid point-in-time recoverability.
Target Audience
Silk targets enterprises utilizing cloud databases such as Oracle, MS SQL Server, and SaaS applications, particularly those in finance, healthcare, insurance, and retail industries.
Features
- Software-defined cloud storage that abstracts the underlying cloud infrastructure
- Shared-compute architecture for accelerated performance and resource efficiency
- Data reduction and performance pooling to eliminate over-provisioning
- Automated data lifecycle management with API-first architecture and REST APIs
- Instant extracts for streamlined ETL processes and accelerated Dev/Test environments
- Active-active architecture and self-healing technology for maximum data durability
- Support for HA and DR across zones, regions, and clouds
- Snapshots for rapid point-in-time recoverability with zero RPO and minimal RTO
- Integration with Microsoft Azure, Google Cloud, Oracle, and MS SQL Server