Hyper-Space
Revolutionizing search with AI, cloud scalability, and real-time precision.. [Contact for Pricing]
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What is Hyper-Space?
Hyper-Space is a cloud-native hybrid search database engineered to deliver unparalleled speed and scalability for data-intensive applications. Built by performance-obsessed engineers, it uses domain-specific computing with custom cloud FPGA hardware (Search Processing Unit or SPU) to shatter the limits of traditional software-based search solutions. The platform enables running any type of search at any scale with real-time data retrieval and no compromise on accuracy, speed, or cost.
Key features include hybrid search combining vector search with lexical search functions like metadata filtering, aggregations, and TF-IDF. Hyper-Space delivers 10x faster performance, 5x higher throughput, 50% lower cost, billion-scale capability, and 4x faster ingestion speed compared to industry benchmarks. The engine uses native Python syntax for CRUD operations, candidate generation, and scoring for similarity and vector searches. It supports elastic scaling, seamless integration, high availability, and enterprise-grade security.
Hyper-Space is designed for data-obsessed teams, AI and generative AI application developers, enterprises dealing with large-scale data retrieval, and companies requiring real-time search at billion-scale. It handling structured and unstructured data including videos, images, and text. The platform is particularly valuable for fraud prevention, recommendation systems, NLP applications, information retrieval, and any search-driven application requiring deterministic, predictable performance under high throughput loads.
The managed database operates as a software-as-a-service model hosted on AWS, with the cloud SPU including tens of dedicated search cores running proprietary instruction sets to filter, rank, and aggregate search results efficiently. Advanced data prefetching avoids cache misses, and the layered storage architecture optimizes in-memory and disk storage usage based on index statistical profiles and field cardinality levels.
Hyper-Space pricing
Pricing model: Freemium
Hyperspace operates as a cloud-native managed database with a software-as-a-service model, priced per usage according to database size and query volume. The company is launching a free, entry-level plan as part of scaling to thousands of instances. Pricing is usage-based rather than sold as instances, with costs optimized to be 50% lower than typical databases. The platform offers cost efficiency by significantly reducing machine time requirements. Contact sales for specific enterprise pricing and custom AI infrastructure solutions.
Hyper-Space pros
- 10x faster search performance than traditional databases
- 5x higher throughput under high load
- 50% lower cost compared to typical databases
- Billion-scale data handling capability
- 4x faster ingestion speed
- Cloud FPGA hardware for unprecedented low latency
- Native Python syntax for easy migration
- Hybrid search combining vector and lexical search
- Metadata filtering and aggregations support
- TF-IDF functionality built-in
- Deterministic and predictable performance
- No garbage collection bottlenecks
- High availability architecture
- Enterprise-grade security compliance
- Elastic seamless scaling from zero to billions
- Low memory footprint with rebuilt index structures
- Advanced data prefetch avoiding cache misses
- Managed SaaS model on AWS
- Support for structured and unstructured data
- Real-time search at billion scale
Hyper-Space cons
- Still in development with limited public release
- Free tier not yet fully available
- Hosted only on AWS currently
- Proprietary technology with vendor lock-in risk
- New platform with smaller community than established databases
- Limited self-hosting options
- Requires migration from existing search solutions
- FPGA hardware dependency may limit flexibility
- Pricing based on usage may be unpredictable
- Fewer third-party integrations than mature platforms
Frequently asked questions about Hyper-Space
What is Hyperspace?
Hyperspace is an elastic compatible cloud-native search database that leverages custom computing power (domain-specific computing with cloud FPGA hardware) so you can run any type of search at any time and scale. It is a cloud-based hybrid search engine powered by cloud FPGA hardware that delivers 10x faster searches than traditional non-accelerated databases.
How does Hyperspace achieve 10x faster performance?
Hyperspace uses domain-specific computing that skips standard software semantics, cache hierarchy, and CPU abstractions. Its cloud SPU includes tens of dedicated search cores running proprietary instruction sets to filter, rank, and aggregate search results. Advanced data prefetching avoids cache misses, and eliminating garbage collection and OS thread schedulers provides deterministic performance hundreds of times faster than general purpose CPUs.
What types of search does Hyperspace support?
Hyperspace supports hybrid search combining vector search with lexical search functions. This includes vector search for high-dimensional data and embeddings, keyword/document search for unstructured data, metadata filtering, aggregations, TF-IDF, and similarity search. You can seamlessly execute both lexical and vector searches within the same query.
What programming language does Hyperspace use?
The Hyperspace engine query syntax is native Python. It allows CRUD operations in native Python syntax with supported functionality for candidate generation and scoring for similarity and vector searches, facilitating seamless transition and natural migration of existing codebases.
What scale can Hyperspace handle?
Hyperspace is purpose-built for billion-scale operations. It can run search at the billion scale while cutting search database costs in half. The platform consistently achieves under 10ms latency at P95 on datasets exceeding 100 million documents and maintains performance under load enabling more queries without delays.
What data types does Hyperspace support?
Hyperspace databases can handle various types of structured and unstructured data including videos, images, and text. The hyperspace index formulates data as key-value pairs where dense and sparse vectors are stored under designated keys. Each record can contain vectors, key-value pairs, or any combination of the two.
Is Hyperspace self-hosted or managed?
Hyperspace is a cloud-native managed database working as a software-as-a-service model. It is hosted on AWS and doesn't sell instances directly - instead it sells access to managed database software running in custom instances. The team designs customized AI infrastructure solutions to help enterprises solve search challenges.
What industries use Hyperspace?
Hyperspace helps companies dealing with large-scale data retrieval, particularly in AI and generative AI applications. Current customers include Forter (fraud prevention), Renovai, and nSure.ai (fraud prevention performance). It's valuable for recommendation systems, NLP and word embedding, information retrieval, and search-driven applications requiring real-time performance.
How does Hyperspace compare to Elasticsearch?
Hyperspace is generally faster than Elastic with 10x faster performance and 5x higher throughput. Unlike Lucene-based data structures that are inefficient in memory footprint due to high-level abstractions, Hyperspace rebuilt the index and data structures from scratch avoiding high-level abstractions for better memory efficiency and retrieval speed, achieving up to 20 times faster than industry benchmarks.
What compliance standards does Hyperspace meet?
Hyperspace is compliant with SOC-2, HIPAA, and GDPR standards. The platform includes enterprise-grade security features and high availability architecture, making it suitable for data-intensive applications in regulated industries requiring real-time data retrieval with no compromise on security and compliance.