Trading-grade data infrastructure

VogazDB

The multi-model, ultra-low-latency database engineered for markets, telemetry, analytics, replay, and audit.

Unify time-series speed, columnar analytics, document flexibility, in-memory execution, and accelerator-ready architecture in one deterministic engine.

LIVE ENGINE p99 target
Time-series Nanosecond indexed
Columnar Vectorized scans
Document Configs and logs
Market Data Ingestion Unified Engine Storage Query Acceleration

Core capabilities

One engine for fast data, deep analytics, and operational records.

01

Time-Series Engine

Optimized for ticks, trades, quotes, telemetry streams, order books, replay, and rollups.

02

Columnar Analytics

Compression-aware storage and vectorized execution for real-time and historical analysis.

03

Document Model

Store strategies, configs, audit records, lifecycle events, and compliance metadata.

04

Unified Query Layer

SQL-style access with time-series operators, JSON paths, and cross-model joins.

05

Auto-Tiered Storage

Route hot data to RAM, recent history to NVMe, and retention data to object storage.

06

Accelerator Ready

Designed for FPGA and hardware-assisted filters, joins, and aggregation paths.

Products

A platform built from production database components.

Start with VogazDB Core, then add low-latency, archive, streaming, management, and accelerator layers as workloads mature.

VogazDB Core

Multi-model database engine with time-series, columnar, document, and UQL capabilities.

VogazDB In-Memory

Hot-path data layer for live market, telemetry, and intraday workloads.

VogazDB Archive

Compliance-grade cold storage with replay, audit, and retention support.

VogazDB Streaming

Real-time ingestion and distribution for tick, event, and telemetry pipelines.

VogazDB Accelerator

Hardware-ready operator pipeline for deterministic execution under load.

Management Console

Operational visibility for storage tiers, health, access control, and deployments.

Architecture

Deterministic data paths for systems where timing and correctness matter.

Sources
Ingestion
Unified Engine
Query + Replay

Lossless Ingestion

Append-only writes preserve exchange sequence, timestamp precision, and replayable market state.

Shared Execution Engine

Time-series, columnar, and document models run through one query and planning layer.

Lifecycle Awareness

Data movement is governed by access frequency, latency sensitivity, and retention policy.

Reliability by Design

Immutable audit logs, write-once streams, and deterministic replay support regulated environments.

Industries

For high-frequency data infrastructure beyond a single market.

Capital Markets

Market data, order events, risk streams, Greeks, P&L, and compliance records.

Exchanges

Tick capture, order-book replay, surveillance data, and market infrastructure analytics.

Banking and Payments

Transaction streams, reconciliation, intraday risk, and immutable audit trails.

Transportation

Railway, metro, aviation, traffic, and fleet telemetry with replayable event history.

Energy and Utilities

Grid load monitoring, SCADA telemetry, anomaly detection, and long-term retention.

Telecom and Cloud

Network telemetry, packet statistics, capacity planning, and real-time fault monitoring.

Government and Defense

Sensor fusion, command telemetry, on-premise deployment, and auditable records.

Industrial IoT

Machine telemetry, quality-control signals, robotics events, and production analytics.

Comparison

Built to reduce database sprawl in latency-sensitive environments.

Capability VogazDB Time-Series DB Columnar DB Document DB
Market-native time-seriesNativeStrongLimitedLimited
Columnar analyticsNativeVariesStrongLimited
Document metadataNativeLimitedLimitedStrong
Unified query layerSingle enginePartialPartialPartial
Replay and auditDesigned inVariesVariesVaries

Benchmarks

Measure performance with transparent, repeatable methodology.

Evaluate latency, throughput, jitter, sustained ingestion, mixed read/write behavior, and replay consistency on comparable hardware.

Latency p50 / p95 / p99 / p99.9
Throughput Writes, reads, mixed workloads
Jitter Tail behavior under sustained load
Replay Correctness across historical state

Enterprise evaluation

Run VogazDB against real workloads before adoption.

Define a 30 to 60 day evaluation around live-like data, deployment constraints, success metrics, and compliance requirements.

Start Evaluation

Contact

Request a technical review.

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