diff --git a/poetry.lock b/poetry.lock
old mode 100644
new mode 100755
index fd335b3..aae7702
--- a/poetry.lock
+++ b/poetry.lock
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+[package.extras]
+test = ["testresources", "testscenarios"]
+
+[[package]]
+name = "toml"
+version = "0.10.2"
+description = "Python Library for Tom's Obvious, Minimal Language"
+optional = false
+python-versions = ">=2.6, !=3.0.*, !=3.1.*, !=3.2.*"
+files = [
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+]
+
+[[package]]
+name = "tomli"
+version = "2.0.1"
+description = "A lil' TOML parser"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
+    {file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
+]
+
+[[package]]
+name = "tqdm"
+version = "4.66.1"
+description = "Fast, Extensible Progress Meter"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "tqdm-4.66.1-py3-none-any.whl", hash = "sha256:d302b3c5b53d47bce91fea46679d9c3c6508cf6332229aa1e7d8653723793386"},
+    {file = "tqdm-4.66.1.tar.gz", hash = "sha256:d88e651f9db8d8551a62556d3cff9e3034274ca5d66e93197cf2490e2dcb69c7"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "platform_system == \"Windows\""}
+
+[package.extras]
+dev = ["pytest (>=6)", "pytest-cov", "pytest-timeout", "pytest-xdist"]
+notebook = ["ipywidgets (>=6)"]
+slack = ["slack-sdk"]
+telegram = ["requests"]
+
+[[package]]
+name = "traitlets"
+version = "5.14.1"
+description = "Traitlets Python configuration system"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "traitlets-5.14.1-py3-none-any.whl", hash = "sha256:2e5a030e6eff91737c643231bfcf04a65b0132078dad75e4936700b213652e74"},
+    {file = "traitlets-5.14.1.tar.gz", hash = "sha256:8585105b371a04b8316a43d5ce29c098575c2e477850b62b848b964f1444527e"},
+]
+
+[package.extras]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
+
+[[package]]
+name = "typing-extensions"
+version = "4.9.0"
+description = "Backported and Experimental Type Hints for Python 3.8+"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
+    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
+]
+
+[[package]]
+name = "tzdata"
+version = "2023.4"
+description = "Provider of IANA time zone data"
+optional = false
+python-versions = ">=2"
+files = [
+    {file = "tzdata-2023.4-py2.py3-none-any.whl", hash = "sha256:aa3ace4329eeacda5b7beb7ea08ece826c28d761cda36e747cfbf97996d39bf3"},
+    {file = "tzdata-2023.4.tar.gz", hash = "sha256:dd54c94f294765522c77399649b4fefd95522479a664a0cec87f41bebc6148c9"},
+]
+
+[[package]]
+name = "unidecode"
+version = "1.3.8"
+description = "ASCII transliterations of Unicode text"
+optional = false
+python-versions = ">=3.5"
+files = [
+    {file = "Unidecode-1.3.8-py3-none-any.whl", hash = "sha256:d130a61ce6696f8148a3bd8fe779c99adeb4b870584eeb9526584e9aa091fd39"},
+    {file = "Unidecode-1.3.8.tar.gz", hash = "sha256:cfdb349d46ed3873ece4586b96aa75258726e2fa8ec21d6f00a591d98806c2f4"},
+]
+
+[[package]]
+name = "urllib3"
+version = "2.2.0"
+description = "HTTP library with thread-safe connection pooling, file post, and more."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "urllib3-2.2.0-py3-none-any.whl", hash = "sha256:ce3711610ddce217e6d113a2732fafad960a03fd0318c91faa79481e35c11224"},
+    {file = "urllib3-2.2.0.tar.gz", hash = "sha256:051d961ad0c62a94e50ecf1af379c3aba230c66c710493493560c0c223c49f20"},
+]
+
+[package.extras]
+brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
+h2 = ["h2 (>=4,<5)"]
+socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
+zstd = ["zstandard (>=0.18.0)"]
+
+[[package]]
+name = "virtualenv"
+version = "20.13.0"
+description = "Virtual Python Environment builder"
+optional = false
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7"
+files = [
+    {file = "virtualenv-20.13.0-py2.py3-none-any.whl", hash = "sha256:339f16c4a86b44240ba7223d0f93a7887c3ca04b5f9c8129da7958447d079b09"},
+    {file = "virtualenv-20.13.0.tar.gz", hash = "sha256:d8458cf8d59d0ea495ad9b34c2599487f8a7772d796f9910858376d1600dd2dd"},
+]
+
+[package.dependencies]
+distlib = ">=0.3.1,<1"
+filelock = ">=3.2,<4"
+platformdirs = ">=2,<3"
+six = ">=1.9.0,<2"
+
+[package.extras]
+docs = ["proselint (>=0.10.2)", "sphinx (>=3)", "sphinx-argparse (>=0.2.5)", "sphinx-rtd-theme (>=0.4.3)", "towncrier (>=21.3)"]
+testing = ["coverage (>=4)", "coverage-enable-subprocess (>=1)", "flaky (>=3)", "packaging (>=20.0)", "pytest (>=4)", "pytest-env (>=0.6.2)", "pytest-freezegun (>=0.4.1)", "pytest-mock (>=2)", "pytest-randomly (>=1)", "pytest-timeout (>=1)"]
+
+[[package]]
+name = "wcwidth"
+version = "0.2.13"
+description = "Measures the displayed width of unicode strings in a terminal"
+optional = false
+python-versions = "*"
+files = [
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
+]
+
+[[package]]
+name = "wheel"
+version = "0.34.2"
+description = "A built-package format for Python"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
+files = [
+    {file = "wheel-0.34.2-py2.py3-none-any.whl", hash = "sha256:df277cb51e61359aba502208d680f90c0493adec6f0e848af94948778aed386e"},
+    {file = "wheel-0.34.2.tar.gz", hash = "sha256:8788e9155fe14f54164c1b9eb0a319d98ef02c160725587ad60f14ddc57b6f96"},
+]
+
+[package.extras]
+test = ["pytest (>=3.0.0)", "pytest-cov"]
+
+[[package]]
+name = "xmltodict"
+version = "0.13.0"
+description = "Makes working with XML feel like you are working with JSON"
+optional = false
+python-versions = ">=3.4"
+files = [
+    {file = "xmltodict-0.13.0-py2.py3-none-any.whl", hash = "sha256:aa89e8fd76320154a40d19a0df04a4695fb9dc5ba977cbb68ab3e4eb225e7852"},
+    {file = "xmltodict-0.13.0.tar.gz", hash = "sha256:341595a488e3e01a85a9d8911d8912fd922ede5fecc4dce437eb4b6c8d037e56"},
+]
+
+[[package]]
+name = "xmod"
+version = "1.8.1"
+description = "🌱 Turn any object into a module 🌱"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "xmod-1.8.1-py3-none-any.whl", hash = "sha256:a24e9458a4853489042522bdca9e50ee2eac5ab75c809a91150a8a7f40670d48"},
+    {file = "xmod-1.8.1.tar.gz", hash = "sha256:38c76486b9d672c546d57d8035df0beb7f4a9b088bc3fb2de5431ae821444377"},
+]
+
+[[package]]
+name = "zipp"
+version = "3.17.0"
+description = "Backport of pathlib-compatible object wrapper for zip files"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
+    {file = "zipp-3.17.0.tar.gz", hash = "sha256:84e64a1c28cf7e91ed2078bb8cc8c259cb19b76942096c8d7b84947690cabaf0"},
+]
+
+[package.extras]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
+testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"]
+
+[metadata]
+lock-version = "2.0"
+python-versions = ">=3.9, <3.13"
+content-hash = "cf6de5423ae462d82798362f48ec842367c50c1d806c5307860a0a2bc9ecad84"
diff --git a/pyproject.toml b/pyproject.toml
old mode 100644
new mode 100755
index 9f2cbfe..6872ab5
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,58 +1,60 @@
-[tool.poetry]
-name = "snews-cs"
-version = "2.2.0"
-description = "An alert application for observing supernovas."
-authors = ["Sebastian Torres-Lara <sebastiantorreslara17@gmail.com>", "Melih Kara <karamel.itu@gmail.com>"]
-license = "BSD 3-Clause"
-readme = "README.md"
-packages = [{include = "snews_cs"}]
-homepage = "https://github.com/SNEWS2/SNEWS_Coincidence_System.git"
-repository = "https://github.com/SNEWS2/SNEWS_Coincidence_System.git"
-documentation = "https://snews-coincidence-system.readthedocs.io/"
-classifiers = [
-    "Development Status :: 2 - Pre-Alpha",
-    "Programming Language :: Python",
-    "Programming Language :: Python :: 3",
-    "Intended Audience :: Science/Research",
-    "Intended Audience :: Developers",
-    "Natural Language :: English",
-    "Topic :: Scientific/Engineering",
-    "Topic :: Scientific/Engineering :: Astronomy",
-    "Topic :: Scientific/Engineering :: Physics",
-    "Operating System :: POSIX",
-    "Operating System :: Unix",
-    "Operating System :: MacOS",
-    "License :: OSI Approved :: BSD License",
-]
-
-[tool.poetry.scripts]
-snews_cs = "snews_cs.__main__:main"
-
-[tool.poetry.dependencies]
-python = ">=3.9, <3.13"
-click = "^8.1.7"
-hop-client = "^0.8.0"
-ipython = "<7.33.0"  # Constrained by snews_pt
-numpy = "^1.26.0"
-pandas = "^2.1.1"
-python-dotenv = "0.19.2"  # Constrained by snews_pt
-pymongo = "^4.5.0"
-slack-sdk = "^3.22.0"
-snews-pt = "^1.3.3"
-matplotlib = "^3.8.0"
-scipy = "^1.11.3"
-
-[tool.poetry.group.dev.dependencies]
-autopep8 = "^2.0.4"
-flake8 = "^6.1.0"
-mongomock = "^4.1.2"
-pytest = "<6.3.0"  # Constrained by snews_pt
-
-[tool.poetry.group.docs.dependencies]
-sphinx = "<5"  # Constrained by snews_pt
-sphinx-pdj-theme = "^0.4.0"
-
-[build-system]
-requires = ["poetry-core"]
-build-backend = "poetry.core.masonry.api"
-
+[tool.poetry]
+name = "snews-cs"
+version = "2.2.0"
+description = "An alert application for observing supernovas."
+authors = ["Sebastian Torres-Lara <sebastiantorreslara17@gmail.com>", "Melih Kara <karamel.itu@gmail.com>"]
+license = "BSD 3-Clause"
+readme = "README.md"
+packages = [{include = "snews_cs"}]
+homepage = "https://github.com/SNEWS2/SNEWS_Coincidence_System.git"
+repository = "https://github.com/SNEWS2/SNEWS_Coincidence_System.git"
+documentation = "https://snews-coincidence-system.readthedocs.io/"
+classifiers = [
+    "Development Status :: 2 - Pre-Alpha",
+    "Programming Language :: Python",
+    "Programming Language :: Python :: 3",
+    "Intended Audience :: Science/Research",
+    "Intended Audience :: Developers",
+    "Natural Language :: English",
+    "Topic :: Scientific/Engineering",
+    "Topic :: Scientific/Engineering :: Astronomy",
+    "Topic :: Scientific/Engineering :: Physics",
+    "Operating System :: POSIX",
+    "Operating System :: Unix",
+    "Operating System :: MacOS",
+    "License :: OSI Approved :: BSD License",
+]
+
+[tool.poetry.scripts]
+snews_cs = "snews_cs.__main__:main"
+
+[tool.poetry.dependencies]
+python = ">=3.9, <3.13"
+click = "^8.1.7"
+hop-client = "^0.8.0"
+ipython = "<7.33.0"  # Constrained by snews_pt
+numpy = "^1.26.0"
+pandas = "^2.1.1"
+python-dotenv = "0.19.2"  # Constrained by snews_pt
+pymongo = "^4.5.0"
+slack-sdk = "^3.22.0"
+snews-pt = "^1.3.3"
+matplotlib = "^3.8.0"
+scipy = "^1.11.3"
+sqlalchemy = "^2.0.32"
+tabulate = "^0.9.0"
+
+[tool.poetry.group.dev.dependencies]
+autopep8 = "^2.0.4"
+flake8 = "^6.1.0"
+mongomock = "^4.1.2"
+pytest = "<6.3.0"  # Constrained by snews_pt
+
+[tool.poetry.group.docs.dependencies]
+sphinx = "<5"  # Constrained by snews_pt
+sphinx-pdj-theme = "^0.4.0"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"
+
diff --git a/snews_cs/_version.py b/snews_cs/_version.py
index d4b750f..6c3c2c9 100644
--- a/snews_cs/_version.py
+++ b/snews_cs/_version.py
@@ -1 +1 @@
-version = '2.2.0'
+version = '2.2.1'
diff --git a/snews_cs/cs_stats.py b/snews_cs/cs_stats.py
index d6598d3..2b5a153 100644
--- a/snews_cs/cs_stats.py
+++ b/snews_cs/cs_stats.py
@@ -3,6 +3,10 @@
 
 def ncr(n, r):
     f = math.factorial
+    # if the HB cache is empty, n-r returns negative number for which factorial is not defined
+    # as a temporary fix, let's return 0
+    if n-r < 0:
+        return 0
     return int(f(n) / f(r) / f(n - r))
 
 def cache_false_alarm_rate(cache_sub_list, hb_cache):
diff --git a/snews_cs/heartbeat_feedbacks.py b/snews_cs/heartbeat_feedbacks.py
index 3feee08..e54f296 100644
--- a/snews_cs/heartbeat_feedbacks.py
+++ b/snews_cs/heartbeat_feedbacks.py
@@ -7,7 +7,8 @@
 from time import sleep
 from .core.logging import getLogger
 from .cs_email import send_warning_mail, send_feedback_mail
-from .snews_hb import beats_path, mirror_csv
+from .snews_hb import beats_path
+from sqlalchemy import create_engine
 
 log = getLogger(__name__)
 
@@ -24,6 +25,13 @@
 # verbose print. Prints only if verbose=True
 vprint = lambda inp, _bool: print(inp) if _bool else None
 
+# SQLite database for the cached heartbeats
+cache_db = os.path.abspath(os.path.join(beats_path, 'cached_heartbeats_mirror.db'))
+cache_engine = create_engine(f'sqlite:///{cache_db}')
+cache_df = None
+
+
+
 class FeedBack:
     """ Once every minute, check the HB of each detector
         If the last heartbeat is from longer than usual, send an email
@@ -37,6 +45,7 @@ def __init__(self, verbose=False):
             self.last_feedback_time[k] = np.datetime64("2022-01-01")
         self.day_in_min = 1440
         self.running_min = 0
+        self.db_found = False
         self.verbose = verbose
         log.info(f"\t> Heartbeat tracking initiated.")
 
@@ -48,15 +57,9 @@ def __call__(self):
         while True:
             # run every minute
             sleep(60)
-            try:
-                df = pd.read_csv(mirror_csv, parse_dates=['Received Times'], )
-            except FileNotFoundError:
-                log.error(f"{mirror_csv} does not exist yet! Maybe `snews_cs run-coincidence` is not invoked?")
-                while not os.path.isfile(mirror_csv):
-                    sleep(60)
-                df = pd.read_csv(mirror_csv, parse_dates=['Received Times'], )
-                log.debug(f"OK {mirror_csv} found! Moving on")
-
+            # The database is continuosly updated, read it every minute
+            # it will wait until it finds a database
+            df = self.read_database() # Received times are already parsed
             self.control(df) # check if a detector is taking longer than usual (mean+3*sigma>)
             self.running_min += 1
             vprint(f"[DEBUG] >>>>> Running minute: {self.running_min}", self.verbose)
@@ -66,6 +69,28 @@ def __call__(self):
                 self.running_min = 0  # reset the counter
                 delete_old_figures()
 
+    def read_database(self):
+        """ Try to read the database, if it is empty (or does not exist) wait
+        """
+        try:
+            # - Try reading cached data from SQL DB
+            cache_df = pd.read_sql_table('cached_heartbeats', cache_engine,
+                                         parse_dates=['Received Times', 'Stamped Times'])
+            if len(cache_df) < 1:
+                raise FileNotFoundError
+            log.debug(f"OK DataBase found! Moving on")
+        except FileNotFoundError:
+            log.error(f"DataBase does not exist yet! Maybe `snews_cs run-coincidence` is not invoked?\n"
+                      f"Sleeping until I find something")
+            sleep(60)
+            self.running_min += 1
+            return self.read_database()
+        # if it passes, that means it found a non-empty database
+        if not self.db_found:
+            log.debug(f"OK DataBase found! Moving on")
+            # log it once, then set db found true
+        self.db_found=True
+        return cache_df
 
     def control(self, df):
         """ Check the current cache, check if any detector
@@ -163,7 +188,8 @@ def plot_beats(df, detector, figname):
     from mpl_toolkits.axes_grid1 import make_axes_locatable
     from matplotlib.colors import LinearSegmentedColormap, Normalize
 
-    latency = pd.to_timedelta(df['Latency'].values).total_seconds()
+    # latency = pd.to_timedelta(df['Latency'].values).total_seconds()
+    latency = df['Latency'].values
     received_times = df['Received Times']  # should be numpy datetime object
     try:
         unique_days_np = np.unique(received_times.astype('datetime64[D]'))
diff --git a/snews_cs/snews_hb.py b/snews_cs/snews_hb.py
index 0de540c..3f15e80 100644
--- a/snews_cs/snews_hb.py
+++ b/snews_cs/snews_hb.py
@@ -4,9 +4,11 @@
 """
 
 import os, json
+import numpy as np
 import pandas as pd
 from datetime import datetime
-import numpy as np
+from sqlalchemy import create_engine
+
 from .cs_utils import set_env, make_beat_directory
 from .core.logging import getLogger
 
@@ -14,13 +16,15 @@
 
 # Check if detector name is in registered list.
 detector_file = os.path.abspath(os.path.join(os.path.dirname(__file__), 'auxiliary/detector_properties.json'))
+
 with open(detector_file) as file:
     snews_detectors = json.load(file)
+
 snews_detectors = list(snews_detectors.keys())
 
+#- Cache of old heartbeats
 beats_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../beats"))
-mirror_csv = os.path.abspath(os.path.join(beats_path, f"cached_heartbeats_mirror.csv"))
-master_csv = os.path.abspath(os.path.join(beats_path, f"complete_heartbeat_log.csv"))
+cache_db = os.path.abspath(os.path.join(beats_path, 'cached_heartbeats_mirror.db'))
 
 def get_data_strings(df_input):
     """ Convert datetime objects to strings
@@ -47,6 +51,34 @@ def to_numpy_datetime(input_datetime):
 ## TODO: make a list of internal heartbeats, and send us = SERVER heartbeats.
 # How many times a day can server log these heartbeats, (what is the livetime of server)
 
+def sanity_checks(message):
+    """ check if the message will crash the server
+        Check  the following
+             - detector frequencies are reasonable
+             - latencies are reasonable
+             - At least one detector is operational
+    """
+    issue = "no issue"
+    for key in ['detector_name', 'detector_status']:
+        if key not in message.keys():
+           issue = f" {key} is not in message keys"
+    if issue == "no issue":
+        if not isinstance(message['Received Times'], np.datetime64):
+            issue = f" {message['Received Times']} is not a np.datetime64 object"
+        if not message['detector_status'].lower() in ['on','off']:
+            issue = f" {message['detector_status']} is neither ON nor OFF"
+        if not message['detector_name'] in snews_detectors:
+            issue = f" {message['detector_name']} is not a valid detector"
+
+    if issue == "no issue":
+        # do not log each time
+        return True
+    else:
+        log.error(f"\t> {message} is received at snews_hb.py but not valid.\n"
+                  f"issue is: {issue}")
+        return False
+
+
 class HeartBeat:
     """ Class to handle heartbeat message stream
     """
@@ -60,7 +92,6 @@ def __init__(self, env_path=None, store=True, firedrill_mode=True):
         self.store = store
         log.info(f"\t> Heartbeats are stored in {beats_path}.")
         make_beat_directory(beats_path)
-        self.stash_time = float(os.getenv("HB_STASH_TIME", "24"))  # hours
         self.delete_after = float(os.getenv("HB_DELETE_AFTER", "7"))  # days
         if firedrill_mode:
             self.heartbeat_topic = os.getenv("FIREDRILL_OBSERVATION_TOPIC")
@@ -68,7 +99,17 @@ def __init__(self, env_path=None, store=True, firedrill_mode=True):
             self.heartbeat_topic = os.getenv("OBSERVATION_TOPIC")
 
         self.column_names = ["Received Times", "Detector", "Stamped Times", "Latency", "Time After Last", "Status"]
-        self.cache_df = pd.DataFrame(columns=self.column_names)
+
+        #- Update the alert cache
+        self.cache_engine = create_engine(f'sqlite:///{cache_db}')
+        self.cache_df = None
+        try:
+            #- Try reading cached data from SQL DB
+            self.cache_df = pd.read_sql_table('cached_heartbeats', self.cache_engine, parse_dates=['Received Times', 'Stamped Times'])
+        except:
+            #- Fall-through if cache does not exist; create it
+            self.cache_df = pd.DataFrame(columns=self.column_names)
+
         self._last_row = pd.DataFrame(columns=self.column_names) #pd.Series(index=self.column_names)
 
     def make_entry(self, message):
@@ -79,10 +120,13 @@ def make_entry(self, message):
         msg = {"Received Times": message["Received Times"],
                "Detector": message["detector_name"]}
 
-        # stamped_time_obj = datetime.fromisoformat(message["sent_time"])
+        # "sent_time" in the message has the following format;
+        #  message["sent_time"] = np.datetime_as_string(np.datetime64(datetime.utcnow().isoformat()), unit='ns')
         stamped_time_obj = np.datetime64(message["sent_time"])
         msg["Stamped Times"] = stamped_time_obj
         msg["Latency"] = msg["Received Times"] - msg["Stamped Times"]
+        # keep latency as integer seconds
+        msg["Latency"] = msg["Latency"].astype('timedelta64[s]').astype(int)
 
         # check the last message of given detector
         detector_df = self.cache_df[self.cache_df["Detector"] == msg['Detector']]
@@ -99,121 +143,23 @@ def make_entry(self, message):
         else:
             self.cache_df = pd.concat([self.cache_df, self._last_row], ignore_index=True)
 
-    def store_beats(self):
-        """ log the heartbeats, and save locally
-
-        """
-        # for now store one master csv in any case
-        self.store_master_csv()
-        if self.store:
-            self.dump_csv()
-            self.dump_JSON()
-
     def drop_old_messages(self):
-        """ Keep the heartbeats for 24 hours
-            Drop the earlier-than-24hours messages from cache
-
-        """
-        # first store a csv/JSON before dumping anything
-        # self.store_beats()
-        curr_time = datetime.utcnow()
-        existing_times = self.cache_df["Received Times"]
-        del_t = (curr_time - existing_times).dt.total_seconds() / 60 / 60 # in hours
-        locs = np.where(del_t < self.stash_time)[0] # keep only times within stash time e.g. 24 hours
-        self.cache_df = self.cache_df.reset_index(drop=True).loc[locs]
-        self.cache_df.sort_values(by=['Received Times'], inplace=True)
-
-    def update_cache_csv(self):
-        """ The daily csv file is kept as a file per day
-            For heartbeat checks I need one that mirrors the current cache.
+        """ Keep the heartbeats for a time period delta.
+            Drop the earlier messages from cache
         """
-        self.drop_old_messages()
-        self.cache_df.to_csv(mirror_csv, mode='w', header=True, index=False)
+        delta = f'{self.delete_after} day'
 
-    def dump_csv(self):
-        """ dump a local csv file once a day
-            and keep appending the messages within that day
-            into the same csv file
+        curr_time = np.datetime64(datetime.utcnow().isoformat()) #pd.to_datetime('now', utc=True)
+        delta_t = curr_time - pd.to_datetime(self.cache_df['Received Times'])
+        select = delta_t < pd.Timedelta(delta)
 
-            Note:
-                This is a temporary back up of the data. Ideally, we need only update_cache_csv
-
-        """
-        today = datetime.utcnow()
-        today_str = datetime.strftime(today, "%y-%m-%d")
-        output_csv_name = os.path.join(beats_path, f"{today_str}_heartbeat_log.csv")
-        if os.path.exists(output_csv_name):
-            self._last_row.to_csv(output_csv_name, mode='a', header=False, index=False)
-        else:
-            self.cache_df.to_csv(output_csv_name, mode='w', header=True, index=False)
-
-    def dump_JSON(self):
-        """ dump a local JSON file once a day
-            and keep appending the messages within that day
-            into the same csv file
-
-            Notes:
-                It is risky at the moment as I overwrite each time instead
-                Ideally we should compare the existing json file with the new one
-                and append the new ones. If the script is re-run in the same day,
-                current version would ignore the previous logs and overwrite a new one
-
-        """
-        # TODO: maybe not needed?
-        # df = get_data_strings(self.cache_df)  # the object types need to be converted for json
-        # curr_data = df.to_json(orient='columns')
-        curr_data  = self.cache_df.to_json(orient='columns')
-        today = datetime.utcnow()
-        today_str = datetime.strftime(today, "%y-%m-%d")
-        output_json_name = os.path.join(beats_path, f"{today_str}_heartbeat_log.json")
-        # if os.path.exists(output_json_name):
-        with open(output_json_name, 'w') as file:
-            #     file_data = json.load(file)
-            #     # append missing keys?
-            # OVERWRITE INSTEAD
-            file.seek(0)
-            json.dump(curr_data, file, indent=4)
-
-    def store_master_csv(self):
-        """ For now, also keep a csv that doesn't distinguish dates
-            Append and save everything
-
-        """
-        if os.path.exists(master_csv):
-            self._last_row.to_csv(master_csv, mode='a', header=False, index=False)
-        else:
-            self.cache_df.to_csv(master_csv, mode='w', header=True, index=False)
-
-    def burn_logs(self):
-        """ Remove the logs after pre-decided time
+        self.cache_df = self.cache_df[select]
+        self.cache_df.sort_values(by=['Received Times'], inplace=True)
 
+    def update_cache(self):
+        """Update the alert cache with whatever we decided to keep.
         """
-        today_fulldate = datetime.utcnow()
-        today_str = datetime.strftime(today_fulldate, "%y-%m-%d")
-        today = datetime.strptime(today_str, "%y-%m-%d")
-        existing_logs = os.listdir(beats_path)
-        if self.store:
-            existing_logs = np.array([x for x in existing_logs if (x.endswith('log.json') or x.endswith('log.csv')) and
-                                      ("complete_heartbeat_log.csv" not in x)])
-
-        # take only dates
-        dates_str = [i.split('/')[-1].split("_heartbeat")[0] for i in existing_logs]
-        dates, files = [], []
-        for d_str, logfile in zip(dates_str, existing_logs):
-            try:
-                dates.append(datetime.strptime(d_str, "%y-%m-%d"))
-                files.append(logfile)
-            except:
-                continue
-
-        time_differences = np.array([(date - today).days for date in dates])
-        older_than_limit = np.where(np.abs(time_differences) > self.delete_after)
-        files = np.array(files)
-        log.debug(f"\t> The following logs are older than {self.delete_after} days and will be removed; \n{files[older_than_limit[0]]}")
-        for file in files[older_than_limit[0]]:
-            filepath = os.path.join(beats_path, file)
-            os.remove(filepath)
-            log.debug(f"\t> {file} deleted.")
+        self.cache_df.to_sql('cached_heartbeats', self.cache_engine, if_exists='replace', index=False)
 
     def display_table(self):
         """ When printed out, these table can be read from the purdue servers
@@ -222,44 +168,13 @@ def display_table(self):
         """
         print(f"\nCurrent cache \n{'=' * 133}\n{self.cache_df.to_markdown()}\n{'=' * 133}\n")
 
-
-    def sanity_checks(self, message):
-        """ check if the message will crash the server
-            Check  the following
-                 - detector frequencies are reasonable
-                 - latencies are reasonable
-                 - At least one detector is operational
-        """
-        issue = "no issue"
-        for key in ['detector_name', 'detector_status']:
-            if key not in message.keys():
-               issue = f" {key} is not in message keys"
-        if issue == "no issue":
-            if not isinstance(message['Received Times'], np.datetime64):
-                issue = f" {message['Received Times']} is not a np.datetime64 object"
-            if not message['detector_status'].lower() in ['on','off']:
-                issue = f" {message['detector_status']} is neither ON nor OFF"
-            if not message['detector_name'] in snews_detectors:
-                issue = f" {message['detector_name']} is not a valid detector"
-
-        if issue == "no issue":
-            # do not log each time
-            return True
-        else:
-            log.error(f"\t> {message} is received at snews_hb.py but not valid.\n"
-                      f"issue is: {issue}")
-            return False
-
-
     def electrocardiogram(self, message):
         try:
-            message["Received Times"] = np.datetime64('now', 'ns') #np.datetime_as_string(np.datetime64('now'), unit='ns')
-            if self.sanity_checks(message):
+            message["Received Times"] = np.datetime64(datetime.utcnow().isoformat()) #pd.to_datetime('now', utc=True)
+            if sanity_checks(message):
                 self.make_entry(message)
-                self.store_beats()
-                self.update_cache_csv()
-                # self.drop_old_messages()
-                self.burn_logs()
+                self.update_cache()
+                self.drop_old_messages()
                 # if all successful, return True. Not logging each time, not to overcrowd
                 return True
             else: