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CypherDB

Documentation

Welcome to the CypherDB docs!

CypherDB is an embedded graph database.

Features:

  • Property Graph data model and Cypher query language
  • Embedded (in-process) integration with applications
  • Columnar disk-based storage
  • Columnar and compressed sparse row-based (CSR) adjacency list and join indices
  • Vectorized and factorized query processing
  • Novel and efficient join algorithms
  • Multi-core query parallelism
  • Serializable ACID transactions

Usability

CypherDB is built for industry use cases. It implements a suite of features that lower the barrier of entry for modeling your data as a graph and querying it in an expressive graph query language. Because CypherDB is an embedded database, it runs within your application process, making it easy to set up and use CypherDB. CypherDB does not require installing any external dependencies or managing it as a DBMS server.

Interoperability

CypherDB is designed to be highly interoperable with a variety of external formats and columnar or relational stores, including Parquet, Arrow, DuckDB, and more. This allows you to easily move your existing data to and from CypherDB, making it a great choice for graph data science, machine learning, and analytics use cases.

Structured property graph model

The data model in CypherDB is based on the property graph model, together with some structure (including node and relationship tables, and a pre-defined schema). This makes it flexible and intuitive to model your existing data as a graph, while also being smart enough to optimize query performance and perform vectorized operations at scale.

Open source

CypherDB is open source and has a permissive MIT license. Check out our GitHub repo and try out CypherDB. And while you’re there, consider giving us a star and spreading the word!