TDengine vs InfluxDB 哪个更易用上手更快-CFANZ编程社区

TDengine 和 InfluxDB 都是时序数据库（Time Series Database）。前者是新兴的黑马，后者是老牌的龙头，这两个哪个更易用，上手更快呢？

下面从最基础的数据写入和查询方面比较一下，由于只对 Python 比较熟悉，就从 Python 出发，通过两者提供的示例代码进行一下对比。

1. InfluxDB

官网文档地址：https://docs.influxdata.com/influxdb/v2.2/api-guide/client-libraries/python/

1.1. 安装连接器

pip install influxdb-client

1.2. 复制示例代码

InfluxDB 提供的代码里面没有提供创建 org 和 bucket 的操作，
相关操作可以参考 InfluxDB 客户端基础操作

import influxdb_client
from influxdb_client.client.write_api import SYNCHRONOUS

bucket = "db01"
org = "test"
token = "xxxxxxxxxxxxxxx"
# Store the URL of your InfluxDB instance
url="http://192.168.0.111:8086"

client = influxdb_client.InfluxDBClient(
    url=url,
    token=token,
    org=org
)

write_api = client.write_api(write_options=SYNCHRONOUS)

p = influxdb_client.Point("my_measurement").tag("location", "Prague").field("temperature", 25.3)
write_api.write(bucket=bucket, org=org, record=p)

query_api = client.query_api()
query = ' from(bucket:"db01")\
|> range(start: -10m)\
|> filter(fn:(r) => r._measurement == "my_measurement")\
|> filter(fn: (r) => r.location == "Prague")\
|> filter(fn:(r) => r._field == "temperature" )'
result = query_api.query(org=org, query=query)
results = []
for table in result:
    for record in table.records:
        results.append((record.get_field(), record.get_value()))

print(results)

PS：直接复制官方的代码运行时报错：

File "influx.py", line 23
    query = ` from(bucket:"my-bucket")\
            ^
SyntaxError: invalid syntax

需要将代码中的反引号修改为单引号才能成功。

1.3. 运行代码

root@cl1:~/influx# python3 influx.py 
[('temperature', 25.3)]

2. TDengine

TDengine 的安装可参考 TDengine学习笔记-集群安装官网文档：https://docs.taosdata.com/2.4/reference/connector/python

2.1. 安装连接器

pip3 install taospy

2.2. 复制示例代码

import taos

conn: taos.TaosConnection = taos.connect(host="192.168.0.11",
                                         user="root",
                                         password="taosdata",
                                         #database="test",
                                         port=6030,
                                         config="/etc/taos",  
                                         timezone="Asia/Shanghai") 

server_version = conn.server_info
print("server_version", server_version)
client_version = conn.client_info
print("client_version", client_version)  # 2.4.0.16


conn.execute("DROP DATABASE IF EXISTS test")
conn.execute("CREATE DATABASE test")
conn.select_db("test")
conn.execute("CREATE STABLE weather(ts TIMESTAMP, temperature FLOAT) TAGS (location INT)")
affected_row: int = conn.execute("INSERT INTO t1 USING weather TAGS(1) VALUES (now, 23.5) (now+1m, 23.5) (now+2m 24.4)")
print("affected_row", affected_row)

result: taos.TaosResult = conn.query("SELECT * from weather")

fields: taos.field.TaosFields = result.fields
for field in fields:
    print(field)  # {name: ts, type: 9, bytes: 8}


data = result.fetch_all()
print(data)

PS：和 InfluxDB 一样，直接运行代码也会报错

connect failed, reason: Invalid database name.

/usr/lib/python3/dist-packages/requests/__init__.py:89: RequestsDependencyWarning: urllib3 (1.26.9) or chardet (3.0.4) doesn't match a supported version!
  warnings.warn("urllib3 ({}) or chardet ({}) doesn't match a supported "
Traceback (most recent call last):
  File "tdengine.py", line 3, in <module>
    conn: taos.TaosConnection = taos.connect(host="192.168.0.11",
  File "/usr/local/lib/python3.8/dist-packages/taos/__init__.py", line 63, in connect
    return TaosConnection(*args, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/taos/connection.py", line 24, in __init__
    self._conn = self._chandle.connect(self._host, self._user, self._password, self._database, self._port)
  File "/usr/local/lib/python3.8/dist-packages/taos/cinterface.py", line 993, in connect
    return taos_connect(host, user, password, db, port)
  File "/usr/local/lib/python3.8/dist-packages/taos/cinterface.py", line 213, in taos_connect
    raise ConnectionError("connect to TDengine failed")

问题在于连接串里面指定了数据库 test，但是此时数据库还没有创建，因此就会报错。
将 database = “test” 注释即可运行。

2.3. 运行代码

root@cl1:~/tdengine# python3 tdengine.py 
server_version 2.4.0.26
client_version 2.4.0.24
affected_row 3
{name: ts, type: 9, bytes: 8}
{name: temperature, type: 6, bytes: 4}
{name: location, type: 4, bytes: 4}
[(datetime.datetime(2022, 6, 15, 10, 45, 50, 787000, tzinfo=<DstTzInfo 'Asia/Shanghai' CST+8:00:00 STD>), 23.5, 1), (datetime.datetime(2022, 6, 15, 10, 46, 50, 787000, tzinfo=<DstTzInfo 'Asia/Shanghai' CST+8:00:00 STD>), 23.5, 1), (datetime.datetime(2022, 6, 15, 10, 47, 50, 787000, tzinfo=<DstTzInfo 'Asia/Shanghai' CST+8:00:00 STD>), 24.399999618530273, 1)]