---
title: Transform Cloud Storage into a Live Analytics Database | Chaos LakeDB
description: Get observability, security analytics, and user insights without retention limits in real-time, assisted by GenAI.
---

Revinate leaves their ELK stack behind to find huge gains with ChaosSearch -- Read More!

[Revinate leaves their ELK stack behind to find huge gains with ChaosSearch -- Read More!

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# Chaos LakeDB

## Built from the ground up to transform your cloud storage into a Live Search+SQL+GenAI Analytics Database

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## Unified Live Data Lake

Live operational and business use cases all leverage the same type of data - now you can collapse them into a single analytic database!

Observability and Security Analytics without retention limits at a fraction of the cost, plus User Insights in real-time across the organization, all enhanced with a natural language assistant powered by [GenAI](https://www.chaossearch.io/ai-assistant).

![Product White Paper](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Resources/Product%20White%20Paper.png?width=158&height=200&name=Product%20White%20Paper.png)

### Product White Paper

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## Transform you cloud storage into stateless live analytics database

### UNIFIED

### INTEGRATED

#### FORMAT

Same on Disk and in Memory

![Format](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Format.svg)

#### STRUCTURE

Same for Search and Relational

![Structure](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Structure.svg)

#### ALGORITHMS

Generic Execution Across Access

![Algorithms](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Algorithms.svg)

#### ARCHITECTURE

Stateless and Auto‑Scalable

![Architecture](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Architecture.svg)

[![Technical Whitepaper CTA](https://www.chaossearch.io/hs-fs/hubfs/C2020/Graphics/Platform/2023/Technical%20Whitepaper%20CTA.png?width=2176&height=138&name=Technical%20Whitepaper%20CTA.png)](https://www.chaossearch.io/resources/technical-whitepaper)

 

## A Single Analytical Database for Live Operational and Business Use Cases

![Chaos LakeDB](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2024/Chaos%20LakeDB%20Graphic_Desktop.png "Chaos LakeDB")

---

## Chaos Index®

Generic data representation for search and relational analytics on cloud storage

### Compression through Representation

Split information into 3 different dimensions to reduce size and entropy

![Data Representation](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Data%20Representation.png)

#### Symbols

Efficient Symbol Encoding (Text-Search)

#### Manifest

Efficient Scope Routing (Query Planner)

#### Locality

Efficient Locality of Reference (Relational)

### Multiplicity of Small

![Multiplicity of Small](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Multiplicity%20of%20Small.png)

Fast 5-20X Compression (size of GZIP)

Small Storage

Small Processing

Small Network

### Performant Search+SQL

![Performant Search+SQL](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Performant%20Search%2BSQL.png)

Unified Efficient Format

Symbols for Efficient Search (e.g. like Lucene)

Locality for Efficient Relational (e.g. like Parquet)

### Optimized for Live Data

Organize data into streams of segments organized by groups, accessible by views

Auto detect and dynamically map schema and tokenize all data

#### Object Group (OG)

![Data Segments](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Data%20Segments.png)

### Live Analytics

![Live Analytics](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Hex%20Diagram.png)

Minute Time to Glass

Seconds Query Resolution

![SQL](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/SQL.png)

Across Search & SQL for first or subsequent queries

### No Schema Management

![No Schema Management](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Hex%20Diagram.png)

Auto Detection and Dynamic Mapping

Ability to Apply Schema

![Schema](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Schema.svg)

Ability to handle flexible formats, the likes of nested fields such as JSON - "a set it and forget it ingestion model"

### Cloud Storage as Backend, not Storage

Segments purposefully designed for fast performance straight from cloud storage

Same format and structure on disk as in memory

![Cloud Storage Backend](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2024/Cloud%20Storage%20Backend.png)

### Best of Cloud Storage

![Best of Cloud Storage](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Hex%20Diagram.png)

$0.02/GB for Unlimited Retention

11 9s Durability

![Cloud Storage](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Cloud%20Storage.svg)

All the benefits of cloud storage, now as a live analytics backend

### Enables Stateless

![Enables Stateless](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Hex%20Diagram.png)

Same Format In Mem and On Disk

Fast First Read Across Access Patterns

![Stateless](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Stateless.svg)

Enables the Chaos Fabric to be stateless and auto-scalable purely based on ingestion and querying needs

---

## Chaos Fabric®

### Serverless and Stateless Fabric

Compute used only to ingest and query data, not data persistence / cache

![Serverless and Stateless Fabric](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2024/Serverless%20and%20Stateless%20Fabric.png)

### No Cost-Retention Trade-off

![Cost](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Cost.svg)

Compute used just for processing, not persistence and all data in cloud storage

### Fast First Read

![Fast Read](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Fast%20Read.svg)

All queries read from cloud storage reducing first read latency penalty

### Generic Compute Workers

Generic containerized workers can do any ingestion and query task

![Dedicated Chaos Managed VPC](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Dedicated%20Chaos%20Managed%20VPC.png)

### Optimized Utilization for Cost-Performance

![Utilization](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Utilization.svg)

Any worker can be used and leased for any ingestion or query task

### Scale without bottlenecks

![Scale](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Scale.svg)

Workers auto age-out to keep them always fresh. Workers auto-scale based on overall worker needs (Chaos Farm)

### Distributed Stream Ingestion and Querying

Distributed stream ingestion Distributed query execution 

![Distributed Stream Ingestion and Querying](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2024/Distributed%20Stream%20Ingestion%20and%20Querying.png)

### Live Ingestion at Scale

![Ingestion](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Ingestion.svg)

Efficient live data ingestion that can auto-scale to handle any spikes

### Search+SQL Analytics via Virtual Views

![Analytics](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Analytics-1.svg)

Integrated Generic Query Engine Chaos Index delivers efficient Search+SQL with Virtual Views for Democratized Data Access

---

## Chaos Farm

### The Final Piece of Third Generation Database Leveraging the Best of The Cloud

How to optimize a stateless fabric's cost-performance for live analytics at scale?

### Distributed Work Operating System

Orchestration and Scheduling of Distributed Work for Ingest and Query task

![Distributed OS](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Distributed%20OS.png)

### Best-in-class Cost-Performance

![Cost Performance](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Cost%20Performance.svg)

Distributed worker allocation for improved utilization leveraging generic workers

### Improved Experience

![Improved Experience](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Improved%20Experience.svg)

Worker allocation prioritized to improve customer experience

### Auto-Scalable Compute

Auto-Scalable Compute Worker Pool Based on Policies and Utilization

![Auto-Scalable](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Auto-Scalable.png)

### Leverage the best of stateless

![Stateless](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Stateless-1.svg)

Ability to scale compute up in high usage periods and down in low usage ones

### Intelligent Auto-Scale for Improved Cost

![Auto-Scale](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Auto-Scale.svg)

Ability to schedule scaling based on time / activity or dynamically based worker utilization

### Centralized Farm to Support Multiple VPCs

Centralized Farm can hold compute for multiple VPCs (customers) without sharing

![Centralized Farm](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Centralized%20Farm.png)

### New Cross-VPC Compute Movement

![Compute Movement](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Compute%20Movement.svg)

Ability to move compute across VPCs allows for centralization of compute that can securely be accessed by multiple VPCs

### Reduced Time to Compute

![Compute Time](https://www.chaossearch.io/hubfs/C2020/Graphics/Platform/2023/Compute%20Time.svg)

Ability to access compute from another VPC allows for latency of seconds to scale rather than minutes from provider

---

## Reduced Time, Cost & Complexity

### Real-Time Analytics & Full Historical Context

- Minute time-to-glass; Seconds query resolution
- Auto-schema detection & dynamic mapping for easy setup & live data use cases
- Unlimited retention without  rehydration needs

### Unmatched Cost-Performance at Scale

- Data only in cloud storage
- Chaos Index® is 5-20x smaller than raw
- Small data = Small compute
- Stateless = Compute just for ingest & query, not store

### Unified Live Search+ SQL+GenAI Analytics

- Single platform across operational & business use cases
- All data stored in customers' cloud storage with granular RBAC
- No sharding, partitioning, schema management including of nested data
- Auto-scaling & seamless upgrades

![ChaosSearch Video Thumbnail](https://www.chaossearch.io/hubfs/C2020/Graphics/Resources/ChaosSearch%20Video%20Thumbnail.jpg) ![Play Button](https://www.chaossearch.io/hubfs/C2020/Icons/White/Play%20Button.svg)

Analyze JSON Logs with ChaosSearch

With ChaosSearch, we no longer have to move or transform our data. That means we don’t have to think about how we’re going to use the data before we access it. It’s just there for us to query. That helps us deliver new opportunities to the business, or discover usage patterns in our systems.

Jeff Kinsherf, SVP, Eng Services and SRE

![Equifax Logo](https://www.chaossearch.io/hubfs/C2020/Logos/Customers/Equifax%20Logo.svg)

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## Interested in scheduling a brief intro call to see how ChaosSearch can accelerate your analytics?

Yes - show me the calendar!

## Future-Proof Your Analytics at Scale

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