Smart Search with Ingext Data Lake
Ingext Search delivers fast, large-window searches across your entire data fabric using FPL (Fluency Processing Language) — from hot Elastic indices to cold Parquet archives — combining speed, scale, and cost efficiency.
Power Search
Keep notables hot in your SIEM and store dense telemetry in low-cost data lakes. Ingext provides a search layer that supports Lucene, SQL, and programmatic MapReduce in JavaScript — letting analysts query, filter, and compute directly across massive datasets without reindexing.
Optimized for Parquet
Designed for large, high-density telemetry data such as firewalls, EDRs, and system logs.
Large Window Performance
Perform time-range and behavioral searches at scale, handling billions of records with ease.
Streaming Data Fabric
Built on Ingext’s streaming architecture, aligning hot data performance with cold data economics.
How Ingext Search Works
A smarter way to query hot, warm, and cold data — with unified access and streaming-aware optimization.
High-Density Parquet Storage
Ingext stores large telemetry data efficiently in Parquet format — ideal for long-term retention and historical analytics.
- Columnar compression reduces cost and footprint
- Optimized for parallel reads and fast filters
- Scales to petabytes with predictable performance
- Ideal for firewall, EDR, and audit telemetry
Processing Language (FPL)
Ingext uses the Fluency Processing Language (FPL), a JavaScript-based query and transformation layer built on ES6. Analysts can go beyond simple searches — writing inline functions to aggregate, enrich, or score records in motion. This allows real-time analysis, complex filtering, and map-reduce logic directly within the data lake.
- Inline JavaScript for aggregation and scoring
- Complex filtering and enrichment in motion
- Map-reduce style analysis across lakes
- Built on ES6 for flexibility and performance
Smart Search Engine
Intelligent query optimization ensures that results are fast and cost-efficient — regardless of where your data resides.
- Automatic partition awareness
- Query cost optimization engine
- Adaptive caching for recent datasets
- Consistent performance across tiered storage
Long Time Range Search Demo
This short video shows how to run a long time range search using Ingext Data Lake.
Why a Streaming Data Fabric Matters
Modern environments generate more telemetry than traditional systems can afford to store or query. A streaming data fabric separates performance data (hot) from historical context (cold), enabling speed where it matters and savings where it counts.
Ingext Search's Role
Ingext Search focuses on the lower-cost, high-volume end of that spectrum — enabling organizations to run fast, wide-window queries across telemetry data stored in Parquet. Instead of rehydrating data into a SIEM, Ingext provides a direct, queryable interface to long-term, high-density datasets.
- Extend visibility beyond standard SIEM retention limits
- Correlate live data with archived telemetry seamlessly
- Eliminate the need for costly reindexing or data duplication
Bring Search Back to Scale
Experience the power of large-window, low-cost search over your telemetry data. Start with the free Community Edition or connect with our team for an enterprise deployment.