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GreptimeDB's Grafana plugin has been upgraded to v3.0.3, adding a Go backend to enable SQL macro interpolation in alert rules, allowing consistent queries in both panels and alerts.
DBeaver Community 26.1.5 has been released, featuring a new dedicated GreptimeDB driver for easier connection and management of time-series data.
A deep-dive blog post walks through a Rust performance PR in GreptimeDB that makes Prometheus read conversion 10x faster, with benchmark reproduction and code analysis.
GreptimeDB v1.2.0-beta.1 is released with major features including JSON2 as a structured column type, Prometheus Remote Write v2 with native histograms, dictionary-encoded series keys for faster queries, and additional hardening/breaking changes.
GreptimeDB introduces a semantic layer that preserves OTLP metadata (instrument kind, unit, temporality) which is normally discarded at ingestion, enabling AIOps tools and LLM agents to understand system topology without guessing from column names.
GreptimeDB v1.1 introduces online repartitioning for existing tables via a single ALTER TABLE statement, eliminating the need for data migration, dual-writes, or application changes. It leverages shared object storage and logical shards to update manifests and routing without moving data between nodes.
This thread explains Observability 2.0, a shift from pre-aggregated metrics to storing wide events with all fields, enabling ad-hoc queries at read time. It highlights the urgency for AI agent observability and how GreptimeDB supports this model.
GreptimeDB is now a native data source in Perses, the CNCF observability dashboard project, supporting metrics via PromQL, logs, traces, and SQL aggregations.
Xiaomi's smart factory replaced Loki with GreptimeDB for log storage, handling billions of rows per month with tailored indexing: Bloom skipping for high-cardinality trace_id, inverted index for low-cardinality fields, and fulltext search on message bodies.
GreptimeDB v1.1 introduces online repartitioning for existing tables, incremental Flow reads, a semantic layer for LLMs, and stability improvements.
GreptimeDB v1.1.0 is released, offering up to 97% faster PromQL queries, 20-40% lower overall query times, and up to 4.5x improvement on TSBS scan-heavy queries, along with online repartitioning for existing tables.
Erxi is welcomed as a new committer to GreptimeDB after shipping several improvements including meta KV write guards, flush-reason propagation, and CSV COPY fixes.
GreptimeDB 1.0 introduces three built-in SQL window functions for anomaly detection (Z-Score, MAD, IQR), enabling anomaly scoring directly in SQL without external services.
GreptimeDB v1.0 introduces Pending Rows Batcher, a three-stage pipeline that moves CPU-intensive work off the Datanode's critical section, improving Prometheus remote write throughput from 1.20M to 2.17M points/sec and reducing Datanode CPU usage by 20%.
GreptimeDB v1.0 integrates DataFusion's dynamic filter pushdown to accelerate TopK queries by pushing runtime bounds to the scan layer, reducing query time from 29 seconds to 0.21 seconds on a 5B-row trace table.
GreptimeDB is a unified database for metrics, logs, and traces, offering OpenTelemetry-native ingestion, SQL/PromQL querying, object storage for cost reduction, and edge-to-cloud deployment.
GreptimeDB's flat-format queries now support prefiltering on any column (tags, fields, timestamps), not just primary keys, delivering up to 4.5x faster performance. Additionally, the mito2 storage engine removed its legacy scan path, cleaning up about 1,800 lines of code.