KalDB is a cloud-native search and analytics engine for log, trace, and audit data. It is designed to easy to operate, cost-effective, and scale to petabytes of data.
- Native support for log, trace, audit use cases.
- Aggressively prioritize ingest of recent data over older data.
- Full-text search capability.
- First-class Kubernetes support for all components.
- Autoscaling of ingest and query capacity.
- Coordination free ingestion, so failure of a single node does not impact ingestion.
- Works out of the box with sensible defaults.
- Designed for zero data loss.
- First-class Grafana support with accompanying plugin.
- Built-in multi-tenancy, supporting several small use-cases on a single cluster.
- Supports the majority of Apache Lucene features.
- Drop-in replacement for most Opensearch log use cases.
- Operate with multiple cloud providers.
- General-purpose search cases, such as for an ecommerce site.
- Document mutability - records are expected to be append only.
- Additional storage engines other than Lucene.
- Support for JVM versions other than the current LTS.
- Supporting multiple Lucene versions.
Project roadmap, architecture diagrams, runbooks, and more are available on the project wiki.
If you are interested in reporting/fixing issues and contributing directly to the code base, please see CONTRIBUTING for more information on what we're looking for and how to get started.
Licensed under MIT. Copyright (c) 2021 Slack.