STOP INDEXING.
START SCANNING.

Nixl skips the index. It stores logs as compact columnar data and scans them in parallel only when you query — so you can keep more data queryable without the index tax.

One email at launch, one when the public benchmark lands. Nothing else.

Built on AWS Billed on data scanned Launching later in 2026

nixl-cli --demo

// Illustrative demo — published benchmarks coming

Why Anti-Index?

Log volumes keep growing. Index-first tools pay a tax on every byte they ingest — build the index, store it, keep it warm. Nixl takes the other path.

vs Elasticsearch

Elastic keeps inverted indexes warm to stay fast, and that footprint grows with what you ingest. Nixl skips the inverted index and scans compact columnar data instead.

vs Datadog

No ingestion tiers or query-volume matrices to plan around. Nixl bills on the data a scan reads, not on what you send in or retain.

vs Splunk

No index queue to wait on before data is searchable. Query raw data across long time ranges as soon as it lands.

vs ClickHouse

ClickHouse is excellent for structured columns. Nixl is built to scan raw, semi-structured log text at scale.

Comparisons describe the architecture. Head-to-head benchmarks published at launch.

AI Native

AI here isn't an assistant bolted onto an old search box — it's part of the product design from day one. At GA, you ask in English and Nixl compiles it to KQL you can read, edit, and keep.

English in, KQL out

Natural language compiles to KQL — inspectable, editable, yours. No black-box queries.

Explained results

Results come with an explanation, not just rows.

Priced before it runs

Scan-cost preview before anything executes — the AI never runs a query you haven't seen priced.

Shipping at GA — same claim discipline as everything else on this page.

Get the benchmark the day it lands.

One email at launch, one when the numbers are public. Nothing else.

// The Idea

A new, anti-index way to store logs.

Most log tools build an inverted index as data arrives, then bill you to keep it warm. Nixl takes the other path: store logs as compact columnar data and scan them in parallel only when you query. Nothing to index on the way in, and nothing to pay for keeping warm.

The Indexing Bottleneck

Traditional tools build an inverted index before data can be searched. As ingest grows, that index work adds cost and delay — and you pay to keep it warm whether you query it or not.

The Anti-Index Advantage

Nixl stores logs as compact columnar data with lightweight skip-indexes, then scans them across parallel workers only when you query. Work happens at query time, on the data a query actually needs.

Better compression and performance.

Skipping the index means less to store and less to keep warm, so keeping data queryable stays cheap and pricing can track real query work instead of retention. We'll lead with measured numbers, not adjectives — a public, reproducible benchmark, including a head-to-head, is the proof artifact. It's coming, and the waitlist gets it the day it lands.