Cassandra
连接数据库
Python可以使用cassandra-driver库连接Cassandra数据库：
from cassandra.cluster import Cluster cluster = Cluster(['127.0.0.1']) session = cluster.connect('my_keyspace') print("Opened Cassandra database successfully") cluster.shutdown()
CRUD操作
接下来，我们将展示在Cassandra中如何进行基本的CRUD操作。
创建（Create）
cluster = Cluster(['127.0.0.1']) session = cluster.connect('my_keyspace') session.execute(""" CREATE TABLE Employees ( id int PRIMARY KEY, name text, age int, address text, salary decimal ) """) print("Table created successfully") cluster.shutdown()
读取（Retrieve）
cluster = Cluster(['127.0.0.1']) session = cluster.connect('my_keyspace') rows = session.execute('SELECT id, name, address, salary FROM Employees') for row in rows: print("ID = ", row.id) print("NAME = ", row.name) print("ADDRESS = ", row.address) print("SALARY = ", row.salary) cluster.shutdown()
更新（Update）
cluster = Cluster(['127.0.0.1']) session = cluster.connect('my_keyspace') session.execute("UPDATE Employees SET salary = 25000.00 WHERE id = 1") print("Row updated successfully") cluster.shutdown()
删除（Delete）
cluster = Cluster(['127.0.0.1']) session = cluster.connect('my_keyspace') session.execute("DELETE FROM Employees WHERE id = 1") print("Row deleted successfully") cluster.shutdown()
Redis
连接数据库
Python可以使用redis-py库连接Redis数据库：
import redis r = redis.Redis(host='localhost', port=6379, db=0) print("Opened Redis database successfully")
CRUD操作
接下来，我们将展示在Redis中如何进行基本的CRUD操作。
创建（Create）
r = redis.Redis(host='localhost', port=6379, db=0) r.set('employee:1:name', 'John') r.set('employee:1:age', '30') r.set('employee:1:address', 'New York') r.set('employee:1:salary', '1000.00') print("Keys created successfully")
读取（Retrieve）
r = redis.Redis(host='localhost', port=6379, db=0) print("NAME = ", r.get('employee:1:name').decode('utf-8')) print("AGE = ", r.get('employee:1:age').decode('utf-8')) print("ADDRESS = ", r.get('employee:1:address').decode('utf-8')) print("SALARY = ", r.get('employee:1:salary').decode('utf-8'))
更新（Update）
r = redis.Redis(host='localhost', port=6379, db=0) r.set('employee:1:salary', '25000.00') print("Key updated successfully")
删除（Delete）
r = redis.Redis(host='localhost', port=6379, db=0) r.delete('employee:1:name', 'employee:1:age', 'employee:1:address', 'employee:1:salary') print("Keys deleted successfully")
ElasticSearch
连接数据库
Python可以使用elasticsearch库连接ElasticSearch数据库：
from elasticsearch import Elasticsearch es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) print("Opened ElasticSearch database successfully")
CRUD操作
接下来，我们将展示在ElasticSearch中如何进行基本的CRUD操作。
创建（Create）
es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) employee = { 'name': 'John', 'age': 30, 'address': 'New York', 'salary': 1000.00 } res = es.index(index='employees', doc_type='employee', id=1, body=employee) print("Document created successfully")
读取（Retrieve）
es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) res = es.get(index='employees', doc_type='employee', id=1) print("Document details:") for field, details in res['_source'].items(): print(f"{field.upper()} = ", details)
更新（Update）
es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) res = es.update(index='employees', doc_type='employee', id=1, body={ 'doc': { 'salary': 25000.00 } }) print("Document updated successfully")
删除（Delete）
es = Elasticsearch([{'host': 'localhost', 'port': 9200}]) res = es.delete(index='employees', doc_type='employee', id=1) print("Document deleted successfully")
Neo4j
连接数据库
Python可以使用neo4j库连接Neo4j数据库：
from neo4j import GraphDatabase driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password")) print("Opened Neo4j database successfully") driver.close()
CRUD操作
接下来，我们将展示在Neo4j中如何进行基本的CRUD操作。
创建（Create）
driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password")) with driver.session() as session: session.run("CREATE (:Employee {id: 1, name: 'John', age: 30, address: 'New York', salary: 1000.00})") print("Node created successfully") driver.close()
读取（Retrieve）
driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password")) with driver.session() as session: result = session.run("MATCH (n:Employee) WHERE n.id = 1 RETURN n") for record in result: print("ID = ", record["n"]["id"]) print("NAME = ", record["n"]["name"]) print("ADDRESS = ", record["n"]["address"]) print("SALARY = ", record["n"]["salary"]) driver.close()
更新（Update）
driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password")) with driver.session() as session: session.run("MATCH (n:Employee) WHERE n.id = 1 SET n.salary = 25000.00") print("Node updated successfully") driver.close()
删除（Delete）
driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password")) with driver.session() as session: session.run("MATCH (n:Employee) WHERE n.id = 1 DETACH DELETE n") print("Node deleted successfully") driver.close()
InfluxDB
连接数据库
Python可以使用InfluxDB-Python库连接InfluxDB数据库：
from influxdb import InfluxDBClient client = InfluxDBClient(host='localhost', port=8086) print("Opened InfluxDB database successfully") client.close()
CRUD操作
接下来，我们将展示在InfluxDB中如何进行基本的CRUD操作。
创建（Create）
client = InfluxDBClient(host='localhost', port=8086) json_body = [ { "measurement": "employees", "tags": { "id": "1" }, "fields": { "name": "John", "age": 30, "address": "New York", "salary": 1000.00 } } ] client.write_points(json_body) print("Point created successfully") client.close()
读取（Retrieve）
client = InfluxDBClient(host='localhost', port=8086) result = client.query('SELECT "name", "age", "address", "salary" FROM "employees"') for point in result.get_points(): print("ID = ", point['id']) print("NAME = ", point['name']) print("AGE = ", point['age']) print("ADDRESS = ", point['address']) print("SALARY = ", point['salary']) client.close()
更新（Update）
InfluxDB的数据模型和其他数据库不同，它没有更新操作。但是你可以通过写入一个相同的数据点（即具有相同的时间戳和标签）并改变字段值，实现类似更新操作的效果。
删除（Delete）
同样，InfluxDB也没有提供删除单个数据点的操作。然而，你可以删除整个系列（即表）或者删除某个时间段的数据。
client = InfluxDBClient(host='localhost', port=8086) # 删除整个系列 client.query('DROP SERIES FROM "employees"') # 删除某个时间段的数据 # client.query('DELETE FROM "employees" WHERE time < now() - 1d') print("Series deleted successfully") client.close()
Snowflake
连接数据库
Python可以使用snowflake-connector-python库连接Snowflake数据库：
from snowflake.connector import connect con = connect( user='username', password='password', account='account_url', warehouse='warehouse', database='database', schema='schema' ) print("Opened Snowflake database successfully") con.close()
CRUD操作
接下来，我们将展示在Snowflake中如何进行基本的CRUD操作。
创建（Create）
con = connect( user='username', password='password', account='account_url', warehouse='warehouse', database='database', schema='schema' ) cur = con.cursor() cur.execute(""" CREATE TABLE EMPLOYEES ( ID INT, NAME STRING, AGE INT, ADDRESS STRING, SALARY FLOAT ) """) cur.execute(""" INSERT INTO EMPLOYEES (ID, NAME, AGE, ADDRESS, SALARY) VALUES (1, 'John', 30, 'New York', 1000.00) """) print("Table created and row inserted successfully") con.close()
读取（Retrieve）
con = connect( user='username', password='password', account='account_url', warehouse='warehouse', database='database', schema='schema' ) cur = con.cursor() cur.execute("SELECT * FROM EMPLOYEES WHERE ID = 1") rows = cur.fetchall() for row in rows: print("ID = ", row[0]) print("NAME = ", row[1]) print("AGE = ", row[2]) print("ADDRESS = ", row[3]) print("SALARY = ", row[4]) con.close()
更新（Update）
con = connect( user='username', password='password', account='account_url', warehouse='warehouse', database='database', schema='schema' ) cur = con.cursor() cur.execute("UPDATE EMPLOYEES SET SALARY = 25000.00 WHERE ID = 1") print("Row updated successfully") con.close()
删除（Delete）
con = connect( user='username', password='password', account='account_url', warehouse='warehouse', database='database', schema='schema' ) cur = con.cursor() cur.execute("DELETE FROM EMPLOYEES WHERE ID = 1") print("Row deleted successfully") con.close()
Amazon DynamoDB
连接数据库
Python可以使用boto3库连接Amazon DynamoDB：
import boto3 dynamodb = boto3.resource('dynamodb', region_name='us-west-2', aws_access_key_id='Your AWS Access Key', aws_secret_access_key='Your AWS Secret Key') print("Opened DynamoDB successfully")
CRUD操作
接下来，我们将展示在DynamoDB中如何进行基本的CRUD操作。
创建（Create）
table = dynamodb.create_table( TableName='Employees', KeySchema=[ { 'AttributeName': 'id', 'KeyType': 'HASH' }, ], AttributeDefinitions=[ { 'AttributeName': 'id', 'AttributeType': 'N' }, ], ProvisionedThroughput={ 'ReadCapacityUnits': 5, 'WriteCapacityUnits': 5 } ) table.put_item( Item={ 'id': 1, 'name': 'John', 'age': 30, 'address': 'New York', 'salary': 1000.00 } ) print("Table created and item inserted successfully")
读取（Retrieve）
table = dynamodb.Table('Employees') response = table.get_item( Key={ 'id': 1, } ) item = response['Item'] print(item)
更新（Update）
table = dynamodb.Table('Employees') table.update_item( Key={ 'id': 1, }, UpdateExpression='SET salary = :val1', ExpressionAttributeValues={ ':val1': 25000.00 } ) print("Item updated successfully")
删除（Delete）
table = dynamodb.Table('Employees') table.delete_item( Key={ 'id': 1, } ) print("Item deleted successfully")
Microsoft Azure CosMos DB
连接数据库
Python可以使用azure-cosmos库连接Microsoft Azure CosMos DB：
from azure.cosmos import CosmosClient, PartitionKey, exceptions url = 'Cosmos DB Account URL' key = 'Cosmos DB Account Key' client = CosmosClient(url, credential=key) database_name = 'testDB' database = client.get_database_client(database_name) container_name = 'Employees' container = database.get_container_client(container_name) print("Opened CosMos DB successfully")
CRUD操作
接下来，我们将展示在CosMos DB中如何进行基本的CRUD操作。
创建（Create）
database = client.create_database_if_not_exists(id=database_name) container = database.create_container_if_not_exists( id=container_name, partition_key=PartitionKey(path="/id"), offer_throughput=400 ) container.upsert_item({ 'id': '1', 'name': 'John', 'age': 30, 'address': 'New York', 'salary': 1000.00 }) print("Container created and item upserted successfully")
读取（Retrieve）
for item in container.read_all_items(): print(item)
更新（Update）
for item in container.read_all_items(): if item['id'] == '1': item['salary'] = 25000.00 container.upsert_item(item) print("Item updated successfully")
删除（Delete）
for item in container.read_all_items(): if item['id'] == '1': container.delete_item(item, partition_key='1') print("Item deleted successfully")
