InfluxDB, high-cardinality time-series, no ceiling.
In short: InfluxDB is a purpose-built time-series database optimized for high-cardinality metrics, telemetry, IoT, and observability data where time is the primary index. InfluxDB 3.x is rebuilt on Apache Arrow, DataFusion, and Parquet storage, with SQL-first querying and the Telegraf agent ecosystem for config-driven ingestion.
InfluxDB 3.x on Apache Arrow + DataFusion + Parquet, Telegraf-driven ingestion, SQL-first queries, object-storage cold tiers, and InfluxDB Cloud Serverless / Dedicated across AWS, Azure, GCP.
InfluxDB · TSM engine
Meta 3 + Data 4 · RF 2
0.00M
20ms
0.00M
80%
Write Throughput
0.00M pts/s[OK] compactor: wrote parquet to object store, 4 partitions
[INF] ingester: persisted arrow batches → parquet, 3ms
[OK] retention: expired 30d partitions in object store
[INF] downsample: 1m→1h scheduled SQL, 12.4M pts
Representative fleet view · illustrative metrics
0+
InfluxDB Clusters Managed
0.99%
Uptime SLA
0×
Median Query Speedup
0%
Avg Storage Compression
Considering InfluxDB?
- ▸ High-cardinality time-series — IoT, observability, or telemetry workload past 10M unique series where 1.x/2.x hit the wall and 3.x is the obvious upgrade.
- ▸ Telegraf-first ingestion — the 300+ plugin ecosystem covers your sources, and you want a purpose-built TSDB instead of bolting time-series onto a relational base.
- ▸ 2.x → 3.x migration just got approved — Flux deprecation, SQL-first queries, Arrow engine rewrite — the team needs a migration runbook before commitment.
JusDB InfluxDB specialists design, deploy, and operate time-series workloads. See InfluxDB consulting →
What we do
What we build with InfluxDB
From cluster design to production query tuning — end-to-end InfluxDB expertise.
Telegraf-Driven Ingestion
300+ input plugins cover system metrics, containers, Kafka, Prometheus, SNMP, cloud-provider metrics — config-driven ingestion that scales without code.
Arrow + DataFusion Engine
InfluxDB 3.x columnar engine on Apache Arrow in-memory + DataFusion query + Parquet storage — billions-of-series cardinality without the 1.x/2.x ceilings.
SQL + InfluxQL
SQL is the primary query language in 3.x; InfluxQL stays for migration continuity from 2.x. BI tools connect via standard drivers without learning a custom DSL.
Object-Storage Cold Tier
Native S3 / GCS / Azure Blob deep storage with hot Arrow caching — predictable retention costs without operator-built tiering rules.
Multi-Cloud Managed Service
InfluxDB Cloud Serverless or Dedicated on AWS, Azure, GCP — managed HA, backup, restore, observability without infrastructure ownership.
Observability Stack Integration
Grafana data-source native, Telegraf agent, Kapacitor processing, Chronograf admin — the focused observability tooling stack that competing TSDBs build around.
Performance
Billions of series, sub-second queries
The InfluxDB 3.x columnar engine on Apache Arrow + DataFusion removes the cardinality ceilings of 1.x/2.x — we tune ingestion, partitioning, and the object-storage cold tier for predictable latency.
Query Performance
After tuning75×
Median speedup
93%
Storage compression
Real cases
Queries we've transformed
9,000ms
120ms
4.2M series — unbounded request_id tag
The fix
Redesigned tag schema; moved high-cardinality data to fields
7,400ms
44ms
Dashboards aggregate raw 1s points on read
The fix
Continuous queries / tasks roll up 1s → 1m → 1h
12,000ms
60ms
90d window scans full-resolution shards
The fix
Retention policy + CQ-backed rollup bucket for long ranges
0.00%
Cluster Uptime
<0s
Failover RTO
0×
Object-Store Copies
High availability
Always on. Engineered that way.
InfluxDB Cloud Dedicated multi-zone deployment, object-storage durability, and Telegraf buffer strategies for reliable delivery — real 99.99% uptime, not a theoretical SLA.
Incident response
A cardinality P1, handled in under 15 minutes.
When a runaway tag explodes cardinality and ingest backs up, a named InfluxDB engineer responds — not a ticket queue. We diagnose from the metrics, throttle the offending series, and prevent recurrence.
Query latency p99 > 9s — dashboards timing out
Named time-series DBA in under 15 min, not a queue
Series cardinality explosion — unbounded tag values
Tag schema redesign + continuous-query downsampling
Cardinality bounded, p99 9s → 120ms — total 14 min
Pre-Migration Assessment
Prometheus / Graphite → InfluxDB
Estimated cutover window: < 10 minutes
Migration
Move to InfluxDB 3.x without the downtime
2.x → 3.x, or another TSDB → InfluxDB. We pre-validate cardinality and schema, rewrite Flux to SQL, dual-write during cutover, and validate query parity before the switch.
InfluxDB service paths
InfluxDB Consulting
Cardinality strategy, Telegraf topology, 2.x → 3.x migration planning, Cloud Serverless vs Dedicated sizing, Flux deprecation runbook — written advisory deliverables.
InfluxDB Migration
2.x → 3.x, TimescaleDB → InfluxDB, and self-managed → Cloud — dual-write cutover, Flux → SQL rewrite, and query-parity validation with zero downtime.
InfluxDB Performance Tuning
Cardinality control, partition and ingest tuning, Arrow + DataFusion query optimisation, and object-storage cold-tier strategy for predictable latency.
TimescaleDB vs InfluxDB
Side-by-side comparison — Postgres-extension vs purpose-built TSDB, SQL vs Flux/InfluxQL, hypertables vs Arrow/Parquet, cardinality, when each fits.
FAQ
InfluxDB — common questions
Ready to evaluate InfluxDB?
Book a 30-minute scoping call. We'll discuss your workload, the cardinality requirements, and the Cloud-vs-self-managed decision before any statement of work.
Explore Our InfluxDB Services
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