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Introducing ZeptoDB

The time-series database market has a gap. kdb+ delivers microsecond performance but costs $100K+/year and requires learning a proprietary language. ClickHouse and InfluxDB are affordable but operate at millisecond latency — 100-1000x slower for real-time workloads. None combine live time-series evidence, agent-scoped memory, prompt cache, and zero-copy Python in one operational layer.

ZeptoDB closes this gap.

Today, that means more than fast tick or sensor queries. ZeptoDB turns live operational timelines into memory for AI agents: raw events, retrieved context, cache hits, model calls, tool calls, and decisions stay replayable with SQL.


ZeptoDB is a C++20 in-memory columnar database built from scratch for microsecond-latency time-series workloads. The core pipeline:

Feed Handler → MPMC Ring Buffer → Column Store → SIMD/JIT Query Engine
WAL (crash recovery)
Parquet HDB (S3/NFS)

Every layer is designed around a single principle: zero-copy, zero-allocation on the hot path.

  • Ingestion: Lock-free MPMC ring buffer with Highway SIMD batch copy — 5.52M events/sec
  • Storage: Arena allocator with columnar layout, no malloc during ingestion or query
  • Execution: LLVM JIT compiles SQL to native code, Highway SIMD for vectorized aggregation
  • Python: pybind11 zero-copy — NumPy arrays reference engine memory directly (522ns)

kdb+ClickHouseInfluxDBZeptoDB
Latencyμsmsmsμs
Ingestion~5M/sec100K/sec50K/sec5.52M/sec
SQL✗ (q lang)InfluxQL✓ Standard SQL
PythonIPC522ns zero-copy
ASOF JOIN
License$100K+/yrOSSOSSBUSL-1.1, free Community

Quant Researchers

ASOF JOIN, VWAP, EMA, xbar — the temporal operations you need, in standard SQL. Python zero-copy for notebooks.

Trading Desks

5.52M ticks/sec ingestion with built-in FIX 4.4, ITCH, and exchange WebSocket parsers.

IoT / Robotics

10KHz sensor ingestion, Window JOIN for sensor fusion, Parquet HDB for historical replay.


ZeptoDB is source-available under BUSL-1.1, with production use allowed by the Additional Use Grant except commercial DBaaS or managed-service resale before the 2030-04-01 Apache-2.0 change date. We’re actively developing:

  • Cluster-consistent Agent Memory routing and replicated memory writes
  • AgentOps dashboards for retrievals, cache events, LLM calls, and tool calls
  • MQTT / OPC-UA connectors for industrial IoT
  • JDBC/ODBC drivers for BI tool integration
  • Managed cloud offering

Try it: Quick Start →