BUG: very very slow when append  long dictionary into HDF5 file
- [x] I have checked that this issue has not already been reported.

- [x] I have confirmed this bug exists on the latest version of pandas.

- [ ] (optional) I have confirmed this bug exists on the master branch of pandas.

---

**Note**: Please read [this guide](https://matthewrocklin.com/blog/work/2018/02/28/minimal-bug-reports) detailing how to provide the necessary information for us to reproduce your bug.

#### Code Sample, a copy-pastable example

```python
# Your code here
import numpy as np
import pandas as pd
from pandas import HDFStore,DataFrame# create (or open) an hdf5 file and opens in append mode

currenttimedata =  {
  "time": "20210101080808",
  "desc": "Ford",
  "status": "success",
  "detail0": "somevalue",
  "detail1": "somevalue",
  "detail2": "somevalue",
  "detail3": "somevalue",
  "detail4": "somevalue",
  "detail5": "somevalue",
  "detail6": "somevalue",
  "detail7": "somevalue",
  "detail8": "somevalue",
  "detail9": "somevalue",
  "detail10": "somevalue",
  "detail11": "somevalue",
  "detail12": "somevalue",
  "detail13": "somevalue",
  "detail14": "somevalue",
  "detail15": "somevalue",
  "detail16": "somevalue",
  "detail17": "somevalue",
  "detail18": "somevalue",
  "detail19": "somevalue",
  "detail20": "somevalue",
  "detail21": "somevalue",
  "detail22": "somevalue",
  "detail23": "somevalue",
  "detail24": "somevalue",
  "detail25": "somevalue",
  "detail26": "somevalue",
  "detail27": "somevalue",
  "detail28": "somevalue",
  "detail29": "somevalue",
  "detail30": "somevalue",
  "detail31": "somevalue",
  "detail32": "somevalue",
  "detail33": "somevalue",
  "detail34": "somevalue",
  "detail35": "somevalue",
  "detail36": "somevalue",
  "detail37": "somevalue",
  "detail38": "somevalue",
  "detail39": "somevalue",
  "detail40": "somevalue",
  "detail41": "somevalue",
  "detail42": "somevalue",
  "detail43": "somevalue",
  "detail44": "somevalue",
  "detail45": "somevalue",
  "detail46": "somevalue",
  "detail47": "somevalue",
  "detail48": "somevalue",
  "detail49": "somevalue",
  "detail50": "somevalue",
}
                  
hdf =HDFStore('storage.h5')

data = {}
for key, value in currenttimedata.items():
        data[key] = [value]

print("data: ", data)

df =DataFrame(data, columns=list(currenttimedata.keys()))
print("df: ", df)
hdf.put('d1', df, format='table', data_columns=True)
print("hdf[d1] 1: ", hdf['d1']) 
for x in range(100):
        print("x: ", x)
        hdf.append('d1', df, format='table', data_columns=True)

print("hdf[d1] 2: ", hdf['d1']) 

hdf.close()# closes the file
```

#### Problem description

[this should explain **why** the current behaviour is a problem and why the expected output is a better solution]

**append very very slow!**

#### Expected Output

#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here leaving a blank line after the details tag]



INSTALLED VERSIONS
------------------
commit           : 2cb96529396d93b46abab7bbc73a208e708c642e
python           : 3.8.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-42-generic
Version          : #46-Ubuntu SMP Fri Jul 10 00:24:02 UTC 2020
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 1.2.4
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.1
pip              : 20.0.2
setuptools       : 44.0.0
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : 4.6.3
html5lib         : None
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 3.0.0
IPython          : None
pandas_datareader: 0.9.0
bs4              : 4.9.3
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.2
numexpr          : 2.7.3
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : None
scipy            : 1.6.3
sqlalchemy       : None
tables           : 3.6.1
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : None

</details>
