Parseable

# Parseable > Parseable is a unified observability platform for logs, metrics, and traces. Built in Rust on Apache Parquet and object storage (S3, GCS, Azure Blob, MinIO), it delivers up to 90% data compression, PostgreSQL-compatible SQL queries, native PromQL support (Enterprise), OpenTelemetry ingestion, and AI-native features — at up to 80x lower cost than Datadog or Splunk. Deployable as a single binary on any cloud or on-premises, with no external dependencies beyond an object store. Parseable is available in three tiers: **OSS** (AGPLv3, self-hosted, free), **Pro** ($0.37/GB, fully managed cloud, 14-day free trial), and **Enterprise** (dedicated infrastructure, BYOC, custom pricing from $999/month). ## Getting started - [Quickstart](https://www.parseable.com/docs/get-started): Three paths — Parseable Cloud Pro (recommended), local Docker, or self-hosted production. - [Architecture](https://www.parseable.com/docs/architecture): Single binary with Prism UI. Runs in standalone (dev) or distributed (production) mode with separate ingestor, query, indexer, and prism node roles. - [Self-Hosted Installation](https://www.parseable.com/docs/self-hosted/installation): Kubernetes (Helm), Docker Compose, or bare metal. Distributed mode requires an object store. - [Configuration](https://www.parseable.com/docs/self-hosted/configuration): All configuration via environment variables — storage backends, TLS, OIDC, performance tuning, distributed mode, and hot tier. ## Ingestion - [Ingestion overview](https://www.parseable.com/docs/ingestion): HTTP(S) JSON or OTLP/HTTP. Required headers: `X-P-Stream` (dataset), `Authorization`. Max payload 10 MiB. Events staged to disk, flushed to Parquet every minute. - [OpenTelemetry](https://www.parseable.com/docs/ingest-data/otel): Native OTLP/HTTP for logs, metrics, and traces — zero configuration. - [Prometheus Remote Write](https://www.parseable.com/docs/ingest-data/prometheus): Ingest metrics from any Prometheus-compatible agent directly into Parseable. - [Auto Instrumentation (Kubernetes)](https://www.parseable.com/docs/ingest-data/auto-instrumentation): PAI operator — zero-config collection of logs, metrics, traces, and events from a K8s cluster. Supports Java, Python, Node.js, .NET. - [eBPF / Zero Instrumentation](https://www.parseable.com/docs/ingest-data/zero-instrumentation): Kernel-level observability via Tetragon — no application code changes needed. - [AI Agents & LLMs](https://www.parseable.com/docs/ingest-data/ai-agents): Observability for OpenAI, Anthropic, LiteLLM, LangChain, LlamaIndex, AutoGen, CrewAI, and any OTel-instrumented framework. Tracks tokens, cost, latency, and reliability. - [Telemetry Agents](https://www.parseable.com/docs/ingest-data/logging-agents): Fluent Bit, Vector, Fluentd, Logstash, Filebeat, Promtail, OTel Collector, Syslog, Log4j, Prometheus. ## Querying - [SQL / Key Concepts](https://www.parseable.com/docs/key-concepts/query): PostgreSQL-compatible SQL via Apache DataFusion. Supports aggregate, window, and scalar functions, regex operators (`~`, `~*`, `!~`), `EXPLAIN ANALYZE`, and `?fields=true` for response metadata. Every query requires a `start`/`end` timestamp. - [SQL Editor](https://www.parseable.com/docs/user-guide/sql-editor): In-browser editor with intelligent auto-complete, query history, saved queries, CSV/JSON export, "add to dashboard", and AI-assisted Text-to-SQL. - [PromQL](https://www.parseable.com/docs/user-guide/promql): *(Enterprise)* Built-in PromQL engine — no separate Prometheus instance needed. Endpoints at `/prometheus/api/v1` follow Prometheus HTTP API conventions, so existing Grafana dashboards and Prometheus-compatible tooling work without changes. Supports 50+ PromQL functions (`rate`, `irate`, `increase`, `histogram_quantile`, `predict_linear`, `holt_winters`, label operations, etc.), 12 aggregation operators, all binary and set operators, vector matching, and subqueries. Integrates with Grafana via the built-in Prometheus […truncated]