Time-Series Databases

Database platforms (open-source and managed cloud) purpose-built for high-ingest time-series and real-time analytics workloads on PostgreSQL, commonly used for telemetry, IoT/sensor data, events, and metrics at large scale.

How do I enable TimescaleDB features on TigerData Tiger Cloud and convert an existing table to a hypertable?

TigerData: how do I set up compression and retention policies for telemetry tables?

How do I configure tiered storage (SSD + S3) in TigerData Tiger Cloud for long retention?

TigerData: what’s the fastest way to migrate from AWS RDS/Aurora PostgreSQL to Tiger Cloud?

TigerData: how do I create a zero-copy fork for debugging an incident or testing a migration?

TigerData pricing: what’s included in Free vs Performance vs Scale, and what will we actually pay?

How do I start a Tiger Cloud trial on TigerData and create my first Postgres service?

TigerData vs Snowflake: cost and latency for near-real-time dashboards on high-ingest event data

TigerData vs InfluxDB: what’s the migration effort and operational overhead difference?

TigerData vs Pinecone for vector search: latency, recall, and total cost if we keep retrieval in Postgres

TigerData vs AWS RDS PostgreSQL: what are the real pricing gotchas and where do costs land?

TigerData vs Google Cloud SQL for Postgres: which handles time-series partitioning and retention better?

TigerData vs Snowflake for time-series analytics: when does Postgres-native win?

TigerData vs Databricks (Iceberg lakehouse): best pattern for real-time + historical telemetry queries?

TigerData vs ClickHouse for real-time analytics on event data — which is easier to operate?

TigerData vs AWS Aurora PostgreSQL for telemetry workloads — cost and scaling differences?

TigerData vs InfluxDB for high-ingest time-series (performance, retention, ops)