The database for our time

To simplify development, reporting and compliance for immutable systems.

Install XTDB Book Demo

SQL that remembers everything,

with corrections and flexible schema,

for fine-grained reporting and time travel:

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Temporal Records

Comprehensive audit over immutable data with SQL:2011

Modern SQL

Rich SQL dialect via FlightSQL & Postgres wire-compatibility

Flexible SQL

First-class handling of semi-structured data

Cloud Native

Read-scalable ACID engine using Apache Arrow + S3

Installation

Run XTDB using Docker and connect via a PostgreSQL wire-compatible connection.

Get Started

# latest release, 100% open source (MPL-2.0 license)

docker run -p 5432:5432 ghcr.io/xtdb/xtdb

# connect via Postgres tooling and drivers, e.g.

psql -h localhost xtdb -c "SELECT 42"

“Why did we make that decision?”

Effective auditability drives trust and learning, supported by:

Immutable records and observations
Handling of errors and delays
Decisions aligned with full context
Easy reflection on past states

Immutability is not enough.
You need time travel.

The status quo

Most systems model the world as it currently is. The history of changes is hard to access and meaningfully query — even basic analysis becomes unreliable when everything is shifting.

Immutability helps, but...

Data lakes and table formats give you immutability, which helps. But snapshots are coarse and few systems attempt to solve the harder aspects of time travel.

The hard truth

If you can't query the past, you will struggle to meet the requirements of the future.

"What was the state of the business as-of 5pm on Friday given the backdated additions and corrections as-of 9am this morning?"

XTDB's bitemporal design provides a robust foundation for auditable reporting, and therefore auditable decision making. This is valued across every level of an organization:

People can only trust systems that they can easily inspect.

Boards

demand accountability throughout IT infrastructure

SOX · COSO · J-SOX

Legal teams

demand protection against liability

GDPR · eDiscovery · CCPA

Engineering teams

demand debuggability and explainability

EU AI Act · SOC 2 · ISO 27001

Business teams

demand access to historical workflows and state

MiFID II · Dodd-Frank

Operations teams

demand remediation capabilities

DORA · PCI DSS

Customers

demand data lineage with corrections

GDPR Art. 16 · CDR

Regulators

demand process oversight and timely reporting

Basel III · Solvency II · SOX §404

Boards

demand accountability throughout IT infrastructure

SOX · COSO · J-SOX

Legal teams

demand protection against liability

GDPR · eDiscovery · CCPA

Engineering teams

demand debuggability and explainability

EU AI Act · SOC 2 · ISO 27001

Business teams

demand access to historical workflows and state

MiFID II · Dodd-Frank

Operations teams

demand remediation capabilities

DORA · PCI DSS

Customers

demand data lineage with corrections

GDPR Art. 16 · CDR

Regulators

demand process oversight and timely reporting

Basel III · Solvency II · SOX §404

People can only trust systems that they can easily inspect.

When XTDB Helps

Change Data Capture

For existing applications

Symptoms

✗ Ad hoc reconciliation processes that lack central transparency
✗ Historical records accepted as "at best an approximation"
✗ Bespoke time-travel logic: soft deletes, timestamp columns, snapshot tables, custom schema versioning

Solution

› Universal history tracking — reduces requirements burden on individual applications
› Native Debezium ingestion for Change Data Integration — as-of queries across many CDC sources
› Decision auditability layer for durable orchestration workflows and agentic workflows

New Development

Build new applications

Pains

✗ Complexity and fragility of ad hoc temporal columns
✗ Cost of building, testing, and maintaining custom history logic
✗ Bitemporal semantics not enforced universally — analytics requires deep schema knowledge
✗ Audit and corrections hard to budget for up front, but requirements loom large

Solution

› Transactional database with automatic bitemporal versioning on every write
› Postgres-compatible APIs — works with existing clients and tools
› Open source and open standards: SQL:2011, Apache Arrow, ADBC

Who XTDB Helps

Energy / Utilities

Virtual Power Plant orchestration

A state-owned energy retailer built a Virtual Power Plant platform to orchestrate thousands of customer-owned solar panels and batteries. Bitemporal history was the only model that could handle late telemetry, retroactive corrections, and the regulatory mandate to reconstruct exactly what the system knew at the moment of every dispatch decision.

Financial Services

KYC compliance at platform scale

A composable platform for regulated financial services needed its KYC component to satisfy both operational and compliance requirements simultaneously — and do it without bespoke history logic.

Business data as evolving time series.

XTDB records a full 'bitemporal' history of data, observable across time:

Some data is always 'on time'
Other data often arrives late
Mistakes must be corrected
Data evolves and 'versions' are retained

Grounded in DBMS History & Semantics

CMU talk hosted by Prof. Andy Pavlo

Watch the full lecture Future Data Systems Seminar Series — Fall 2025, featuring MotherDuck, Snowflake, Databricks etc.

An architecture for decision intelligence.

Transactional data with perfect memory:

History without headaches - avoid custom versioning, 'soft deletes', and brittle data pipelines
Object store LSM-Tree design with bitemporal historical partitioning for durability, scalability, and cost-effective retention
Postgres-compatible SERIALIZABLE SQL transactions with optimistic concurrency
Fine-grained interval versioning with Apache Arrow for temporal analytics and scale-out compute