A note from our founder

“We didn’t start with a product idea. We started with a problem we couldn’t put down.”

Twenty years building Axcient for 5,000+ MSPs meant fighting an ocean of logs every day. SparkLogs is the data layer we wished we had: petabyte scale, near zero overhead to manage, and with automatic pattern analysis and data extraction.

AI has now become a force multiplier for human talent. Our mission: give engineers AI superpowers, with “X-ray vision” across all systems, so they can resolve issues in record time and be home in time for dinner.

Kevin Hoffman

Founder & CEOPreviously co-founder, Axcient

Our story

Ticket #4781 · same data, two paths

FILE SERVER IS INTERMITTENTLY SLOW

"Started this morning, no recent changes reported."

Manual today

Senior engineer, by hand

~60 min

With SparkLogs

Same engineer plus AI partner

~5 min

Time reclaimed12× faster

Find Out How

Petabytes of Log Data

Schemaless

Ingestion is "point and shoot" — fields don't have to be configured, just send data. Capture complex JSON data with each log event. No field limits.

AutoExtract

Auto-extract semi-structured and JSON data from plain text. Auto-detect field types. Auto-extract IP addresses, timestamps, and bracketed values.

Visual Data Exploration

Visualize patterns across billions of events.
Instant zoom-in, filter, search, and export.
Easily sift through huge query results.

Petabyte Scale

Fully managed in our cloud.
Always on, infinitely scalable.

Ingest Anything

Open-source ingestion agents for files, Kubernetes, syslog, journald, Kafka, Docker, and more.
OpenTelemetry, vector.dev, filebeat, Logstash, Alloy.
Or ingest via REST, OTLP/HTTP, or elasticsearch API.

Enterprise Ready

Data encrypted at rest and in-transit.
SSO in every plan. Role-based access control.
Optionally use your own Google cloud tenant.

Petabyte-scale Querying

Analyze datasets with 100s of *billions* of events in less than 10 seconds.
SQL-like query language with custom fields, array unfolding, and advanced operators.
Full-text index provides fast search over any time scale for “needle-in-PB-haystack” type searches.
Adaptive-scale querying to explore any time-scale in seconds, then easily zoom-in to refine areas of interest.

Example of Massive Scale Adaptive Querying Engine

Zero Config + Schemaless + AutoExtract

No indexes to configure, no field schemas, no parsing rules. Point and shoot ingestion.
Infinite custom fields. Infinite cardinality. Send plain text or (semi) structured data.
AutoExtract structured data from plain text. Automatic category and pattern classification.
Automatic GeoIP lookups on IP addresses and foreign currency conversion.

Try it out for yourself on your own log line!

OpenTelemetry-Native Ingestion

Native OTLP/HTTP ingestion for OpenTelemetry logs, supporting JSON and protobuf payloads and eight compression encodings.
Works with the OpenTelemetry Collector, every OTel SDK (Python, Go, Node.js, Java, .NET, Rust, …), and any OTLP-compliant shipper.
Smart auto-derivation of three levels of pivot fields (source, service, app) from your OTel Resource attributes.
Built-in resilience: request dedup, clock-drift correction, and large payload support.
Schemaless and infinite-cardinality by design — your wide events stay wide.

Automatic Syslog Parsing

Automatic parsing of syslog data in known and unknown formats with zero configuration.
Supports RFC3164 (and its many variants), RFC5424, Linux, FreeBSD, and many proprietary
formats such as Cisco, Juniper, SonicWall, WatchGuard, Fortinet, and more!

Interactive Data Exploration

Interactive histogram with live zooming and instant severity filtering.
Filter by data hierarchy (organization) and data sources; pivot to filter on any field.
Explore events at any point within query time window, with infinite bi-directional scrolling.
Side-by-side context viewer (e.g., matching errors on left, surrounding full context on right).
Copy logs to clipboard or download first million matches with shareable link.

Pattern Analysis

Automatically classify log events into prototypical patterns with zero configuration.
Identify top application error patterns, then pivot to see examples in context.
Analyze top 10,000 values for any (custom) field over any window of time.

How Ingestion Works

Use your favorite open-source tools like OpenTelemetry, vector.dev, filebeat, Logstash, Alloy.
Or ingest via our open APIs: HTTPS/REST, OTLP/HTTP, elasticsearch, or Loki Push.

Unreal Engine Analytics & Logs

For game studios using Unreal Engine, collect & analyze analytics events at massive scale.
Use daily snapshots of analytics to optimize DAU, engagement, and revenue.
Gain full access to raw and snapshot data for your own machine learning models.
Ingest and query game logs from backend servers and dev environments.
Effortless implementation with our field-proven Unreal Engine plugin.

Replicate to Your Data Lake

Replicate a copy of all your data to any cloud storage bucket.
Data is stored compressed in a ready-to-query Parquet hive-partitioned format.
Use to efficiently meet retention requirements of HIPAA, FINRA, SEC, or CFTC
while also delivering a queryable archive for forensics and analysis.

Game Changing Cost Savings

Illustrative example for a company that ingests 20 TB/month, retains logs for 30 days, and makes 200 queries/day.
We offer 3 different pricing plans to meet the needs of organizations of any size from GB-scale to PB-scale.

SparkLogs delivers up to 25x cost savings vs competitors. For an organization ingesting 20 TB/month, SparkLogs costs between $2,900/month and $7,800/month depending upon the service plan, vs competing solutions that cost between $16,100/month and $71,905/month.