Stop fighting cardinality limits.

Stop worrying about single points of failure.

Start storing more, querying faster, and scaling effortlessly - without changing a single line of your existing code.

Keep using what you love. Get what you actually need.
Your monitoring, IoT, observability, or analytics stack already speaks InfluxDB v1 Line Protocol and InfluxQL.
HyperbyteDB is a full drop-in replacement:

• Same `/write` and `/query` endpoints
• Same InfluxQL you know (aggregates, derivatives, moving averages, GROUP BY time(), subqueries, regex measurements, and more)
• Same clients and agents (Telegraf, Grafana, etc.)
• Continuous Queries
• High Availability Replication

Just point them at HyperbyteDB and go.

But behind the scenes, you get a completely re-engineered engine built for the realities of modern workloads.

Solutions

Optimizing Energy Systems with HyperbyteDB

Real-time monitoring and analytics for smart grids, renewables, and utility operations The energy sector is undergoing massive transformation — from renewable integration and smart metering to predictive maintenance and demand-response programs. These initiatives generate vast amounts of time series data that must be ingested, stored, and analyzed at scale with high

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Powering Real-Time Financial Analytics with HyperbyteDB

How a high-performance time series database transforms trading, risk management, and market intelligence Financial markets move at lightning speed. Every millisecond counts when processing tick data, monitoring portfolios, detecting anomalies, or running complex risk calculations. Traditional databases often buckle under the volume, velocity, and cardinality of financial time series data.

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Observability and Monitoring with HyperbyteDB

High-cardinality metrics at scale — without the pain of traditional time series databases Modern applications are distributed, dynamic, and complex. Engineering and SRE teams need deep visibility into system health, application performance, user experience, and infrastructure behavior — in real time. This generates enormous volumes of time series data: metrics, events, and

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Unlocking Scalable IoT Insights with HyperbyteDB

How a modern time series database powers the Internet of Things revolution In today’s connected world, IoT devices generate massive volumes of time-stamped data. From smart factories and agricultural sensors to fleet management and smart cities, organizations need a robust solution to ingest, store, and analyze this data in real

Hyperbyte CloudAustin

What changes for you?

Store dramatically more data
High-cardinality is no longer a problem. Tag every device, user, session, or sensor without watching your database OOM or slow down. HyperbyteDB handles **insanely high cardinality** gracefully thanks to Parquet columnar storage and an embedded ClickHouse query engine.

Query faster, even on huge datasets
Sub-second analytical queries on billions of points. Low-latency responses even when scanning across massive time ranges or complex aggregations. Your dashboards feel snappy again.

Scale horizontally with true master-master clustering
Every node accepts writes. Add nodes and get linear capacity without complex sharding logic or downtime. Built-in replication keeps your data highly available and consistent.

Write at insane speeds
Over 1 million points per second on modest hardware - with full durability through RocksDB WAL and background flushing to optimized Parquet files.

Real performance, real results

These are just the early pipeline numbers. End-to-end ingestion and queries scale even better in production thanks to the columnar architecture.