11 pointsby mineev2 hours ago2 comments

mineev2 hours ago
Why it matters:
→ 3x faster than nearest competitors. Rust + Apache DataFusion + Arrow do the heavy lifting.
→ Exactly-once delivery with WAL. No data loss, no duplicates - guaranteed.
→ Your data stays in open formats you control. No vendor lock-in. Ever.
→ Query logs through Loki-compatible API - works with your existing Grafana setup.
→ Ingest via standard OpenTelemetry (gRPC/HTTP). No proprietary agents.
→ Your data is in Iceberg tables - query it with Trino, Spark, Flink, DuckDB, or any tool in the Iceberg ecosystem.
→ Your observability data becomes a first-class asset of your data lake alongside business analytics.
→ Scale ingest, query, and storage independently. Full compute-storage separation provides stateless deployment.
- denchick2 hours ago
  > 3x faster than nearest competitors
  Wow, that's awesome! Do you have any public benchmarks?
  - sprosvirnin2 hours ago
    There will be a series of articles on Linkedin https://www.linkedin.com/company/icegatetech in the near future, where we will tell you more about the technical side and show benchmarks.
denchick2 hours ago
How do you achieve fault tolerant?
- sprosvirninan hour ago
  Since the state is not stored in compute, fault tolerance is more likely to be transferred to S3. For compute fault tolerance (ingest + query), it is better to place 3 nodes in different AZ or different regions.