Memgraph Zero

Zero ETL. Query data where it lives.

Memgraph Zero is a product line from Memgraph built on a simple idea: your data should stay where it is, and you should still be able to query it as a graph. No Extract, Transform, Load pipelines. No moving terabytes into a new silo. No waiting for batch jobs to finish before you can ask a question.

Instead, Memgraph Zero connects directly to the systems you already run: graph databases, relational warehouses, data lakes, and streaming platforms, and lets you query across them using standard graph query languages. You get graph intelligence without the engineering tax of maintaining another data pipeline.

Powered by MemGQL

The first component of Memgraph Zero is MemGQL, a federated GQL query engine that translates ISO-standard graph queries into the native languages of each backend. Whether your data lives in PostgreSQL, ClickHouse, DuckDB, or Iceberg, you name it, MemGQL speaks the protocol, pushes down the work, and returns unified results. One query layer. No new language to learn. No data movement required.

MemGQL is just the beginning. Memgraph Zero is designed as an extensible platform. Several advanced capabilities are already available through MemGQL, with additional components for real-time graph computation coming in future releases.

Use Cases

Memgraph Zero solves specific problems that teams face when data is scattered across systems and compliance boundaries:

• Public-Private Data — Keep sensitive data sovereign while querying it alongside public knowledge graphs. Private customer records stay in PostgreSQL; public catalogs live in Memgraph. One GQL query joins both without moving regulated data.

• Enterprise Context Sharing — Share canonical context across departments without forcing every team into the same database.

• Distributed Compute — Spread graph computation across multiple nodes for workloads that exceed a single instance.

• Agentic Data Access — Give AI agents a single semantic layer to discover and query any data in the organization using standard GQL.

See all use cases for working examples and Docker Compose setups you can run yourself.

Why Zero ETL matters

The industry has spent the last decade building ever-more-complex data pipelines. Memgraph Zero takes the opposite approach: connect, don’t collect. Query in place, don’t copy. This means:

• No pipeline maintenance - eliminate the engineering hours spent keeping ETL jobs alive
• No data staleness - query the live source, not yesterday’s extract
• No storage bloat - stop duplicating data into yet another warehouse
• Faster time to insight - ask graph questions across your existing infrastructure today

Memgraph Zero enters a market category that is already primed for this approach. The difference is in the execution: a real-time graph engine, GQL standards compliance, and a query layer that unifies relational, graph, and lakehouse systems under one familiar interface.