Run concurrent transactions
The driver is compatible with Python’s
asyncio, which allows implementing concurrent workflows.
To interact with the database in an asynchronous way, create an
The workflow is very similar to the synchronous version, except that you must use
await on all async calls, and define as
async all functions that should be awaited.
If you need causal consistency across different transactions, use bookmarks.
import asyncio from neo4j import AsyncGraphDatabase URI = "<URI for Neo4j database>" AUTH = ("<Username>", "<Password>") async def get_people(tx): result = await tx.run("MATCH (a:Person) RETURN a.name AS name") records = await result.values() return records async def main(): async with AsyncGraphDatabase.driver(URI, auth=AUTH) as driver: async with driver.session(database="neo4j") as session: records = await session.read_transaction(get_people) print(records) asyncio.run(main())
Async implements a concurrency model, but it is not the only possible one.
Multithreading is also possible, although
|There is a known issue with Python 3.8 and the async driver where it gradually slows down. It is generally recommended to use the latest supported version of Python for the best performance, stability, and security.|
A Long Term Support release is one guaranteed to be supported for a number of years. Neo4j 4.4 is LTS, and Neo4j 5 will also have an LTS version.
Aura is Neo4j’s fully managed cloud service. It comes with both free and paid plans.
Driverobject holds the details required to establish connections with a Neo4j database. Every Neo4j-backed application requires a
Cypher is Neo4j’s graph query language that lets you retrieve data from the graph. It is like SQL, but for graphs.
Awesome Procedures On Cypher (APOC) is a library of (many) functions that can not be easily expressed in Cypher itself.
Bolt is the protocol used for interaction between Neo4j instances and drivers. It listens on port 7687 by default.
Atomicity, Consistency, Isolation, Durability (ACID) are properties guaranteeing that database transactions are processed reliably. An ACID-compliant DBMS ensures that the data in the database remains accurate and consistent despite failures.
- eventual consistency
A database is eventually consistent if it provides the guarantee that all cluster members will, at some point in time, store the latest version of the data.
- causal consistency
A database is causally consistent if read and write queries are seen by every member of the cluster in the same order. This is stronger than eventual consistency.
The null marker is not a type but a placeholder for absence of value. For more information, see Cypher Manual — Working with
A transaction is a unit of work that is either committed in its entirety or rolled back on failure. An example is a bank transfer: it involves multiple steps, but they must all succeed or be reverted, to avoid money being subtracted from one account but not added to the other.
Was this page helpful?