Apache Druid
druid.apache.orgIngest streaming or batch data into an analytics database built for fast interactive queries.
Ingest streaming or batch data into an analytics database built for fast interactive queries.
Connect apps, automate work, and run AI agents on one platform
Collect infrastructure and application telemetry, then explore logs, traces, metrics, and user behavior together.
Stores and searches application logs with LogsQL, a built-in explorer, and integrations for common collectors.
Collect logs, metrics, traces, and profiles in a unified observability platform.
Standardized digital-asset trade, derivatives and order-book datasets
Centralize application and infrastructure logs for search, monitoring, and troubleshooting in a managed cloud analytics service.
Explore SQL-connected data with charts, dashboards and a SQL workspace.
Unify marketing data for branded reports, dashboards and scheduled analysis.
Run a SQL time-series database for ingesting, querying, and retaining timestamped events.
Collect cloud workload telemetry and build monitors for Kubernetes and Linux environments.
A managed GridDB service for collecting and querying time-series data from applications and devices.
Combine network flow, device, cloud, and synthetic telemetry to investigate traffic and service performance.
Bring logs, metrics, traces, and infrastructure monitoring into one observability workspace.
A distributed columnar store for analytical workloads on data that continues to change.
Correlate OpenTelemetry metrics, traces, and logs in a shared observability workspace.
Collect OpenTelemetry signals, control their volume, and create operational checks from one observability workspace.
Trace Python services and AI workflows with correlated OpenTelemetry data.
A managed cloud database for transactional SQL, analytics, and multi-model workloads.
Query relational, JSON, geospatial, text, and time-series data through one distributed SQL database.
Use a managed Prometheus-compatible backend for metrics from EKS and other Kubernetes clusters.
Make tail-based sampling decisions across complete traces before forwarding telemetry.
AI document processing that extracts structured data from files
Collect and analyze metrics, logs, and traces, then alert or automate a response to service problems.