Distributed Search
Across Any Data Lake
Execute searches directly where data lives using LocalSearch, and extend seamlessly across clusters and regions with Federated Search. No rehydration. No re-indexing. Real-time results at data-lake scale.
Ask Anything.
Get the Query.
ShyftQL AI turns your questions into powerful search queries instantly. No syntax. No guesswork. Just describe what you need—and run it.
Search Without Index Limits
Shyft Search decouples search from indexing—executing queries directly on structured, semi-structured, and raw data in object storage.
Index-Optional Search
Query Parquet, JSON, CSV, and raw logs directly from S3, Ceph, MinIO, Azure Blob, or GCS—no mandatory indexing or rehydration.
Distributed Execution
Searches are pushed down to data nodes where data lives. Parallel execution delivers fast results at massive scale.
Hot, Warm, Cold, Frozen
Seamlessly search across all data tiers—from hot local storage to frozen object stores—through a single query interface.
Streaming Results
Results stream back as they are found. Start investigating immediately without waiting for full scans.
Schema-Aware Search
Works natively with Shyft Analyzer templates and normalized schemas, enabling fast, accurate field-based queries.
No Vendor Lock-In
Own your data in open formats. Search anywhere, migrate anytime, and avoid proprietary indexes.
Shyft Search Capabilities
Real Shyft Search workflows — from configuration to federated search and AI-powered queries.
How Shyft Search Works
A distributed, push-down search engine optimized for data-lake scale.
Query Orchestration
Search requests are parsed, optimized, and split by time, source, and storage tier.
Distributed Execution
Worker nodes execute searches close to data using columnar scans and predicate pushdown.
Streaming Merge
Partial results stream back and are merged in real time, enabling immediate analysis.
Unified Results
Results delivered through a single UI and API, regardless of where data resides.
Designed for Security & Observability
Shyft Search complements existing SIEMs and analytics platforms instead of replacing them.
🛡️ Security Investigations
Deep historical searches during incident response — no rehydration or index restore needed.
📈 Observability & SRE
Analyze trends, errors, and anomalies across months or years of retained data.
💰 Cost Optimization
Keep data in low-cost object storage while retaining full searchability.
🔄 SIEM Offload
Offload historical and exploratory searches from expensive SIEM platforms.
Search Everything. Store Anywhere.
Break free from index limits and regain control of your security and observability data.