diff --git a/poetry.lock b/poetry.lock
index 61b673e..fb7b3e8 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
 
 [[package]]
 name = "alabaster"
@@ -130,33 +130,33 @@ yaml = ["PyYAML"]
 
 [[package]]
 name = "black"
-version = "24.3.0"
+version = "24.4.2"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -174,39 +174,6 @@ d = ["aiohttp (>=3.7.4)", "aiohttp (>=3.7.4,!=3.9.0)"]
 jupyter = ["ipython (>=7.8.0)", "tokenize-rt (>=3.2.0)"]
 uvloop = ["uvloop (>=0.15.2)"]
 
-[[package]]
-name = "blosc2"
-version = "2.0.0"
-description = "Python wrapper for the C-Blosc2 library."
-optional = false
-python-versions = ">=3.8, <4"
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-
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-msgpack = "*"
-
 [[package]]
 name = "certifi"
 version = "2024.2.2"
@@ -490,63 +457,63 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
 
 [[package]]
 name = "coverage"
-version = "7.4.4"
+version = "7.5.0"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
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 version = "1.8.1"
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 [[package]]
 name = "exceptiongroup"
-version = "1.2.0"
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 [package.extras]
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+version = "2.5.36"
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 research = ["entsoe-py (>=0.3.2)", "lxml (>=4.6.2)", "python-dotenv (>=0.15.0)", "xmltodict (>=0.12.0)"]
 
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-
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 name = "platformdirs"
-version = "4.2.0"
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 [package.extras]
 test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
 
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+    {file = "regex-2024.4.16.tar.gz", hash = "sha256:fa454d26f2e87ad661c4f0c5a5fe4cf6aab1e307d1b94f16ffdfcb089ba685c0"},
 ]
 
 [[package]]
@@ -2950,18 +2734,18 @@ test = ["asv", "gmpy2", "mpmath", "pooch", "pytest", "pytest-cov", "pytest-timeo
 
 [[package]]
 name = "setuptools"
-version = "69.2.0"
+version = "69.5.1"
 description = "Easily download, build, install, upgrade, and uninstall Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "setuptools-69.2.0-py3-none-any.whl", hash = "sha256:c21c49fb1042386df081cb5d86759792ab89efca84cf114889191cd09aacc80c"},
-    {file = "setuptools-69.2.0.tar.gz", hash = "sha256:0ff4183f8f42cd8fa3acea16c45205521a4ef28f73c6391d8a25e92893134f2e"},
+    {file = "setuptools-69.5.1-py3-none-any.whl", hash = "sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32"},
+    {file = "setuptools-69.5.1.tar.gz", hash = "sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
-testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy (>=0.9.1)", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "pygments-github-lexers (==0.0.5)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-favicon", "sphinx-inline-tabs", "sphinx-lint", "sphinx-notfound-page (>=1,<2)", "sphinx-reredirects", "sphinxcontrib-towncrier"]
+testing = ["build[virtualenv]", "filelock (>=3.4.0)", "importlib-metadata", "ini2toml[lite] (>=0.9)", "jaraco.develop (>=7.21)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "mypy (==1.9)", "packaging (>=23.2)", "pip (>=19.1)", "pytest (>=6,!=8.1.1)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-home (>=0.5)", "pytest-mypy", "pytest-perf", "pytest-ruff (>=0.2.1)", "pytest-timeout", "pytest-xdist (>=3)", "tomli", "tomli-w (>=1.0.0)", "virtualenv (>=13.0.0)", "wheel"]
 testing-integration = ["build[virtualenv] (>=1.0.3)", "filelock (>=3.4.0)", "jaraco.envs (>=2.2)", "jaraco.path (>=3.2.0)", "packaging (>=23.2)", "pytest", "pytest-enabler", "pytest-xdist", "tomli", "virtualenv (>=13.0.0)", "wheel"]
 
 [[package]]
@@ -3010,13 +2794,13 @@ files = [
 
 [[package]]
 name = "spectrum-fundamentals"
-version = "0.5.1"
+version = "0.5.2"
 description = "Fundamental functions, annotation pipeline and constants for oktoberfest"
 optional = false
 python-versions = "<3.11.0,>=3.8.0"
 files = [
-    {file = "spectrum_fundamentals-0.5.1-py3-none-any.whl", hash = "sha256:08a7fad3f32de1563146fdd7131754c37dc1d7044e11dda3d4924bea4b2df2cb"},
-    {file = "spectrum_fundamentals-0.5.1.tar.gz", hash = "sha256:44c4886e9da966d1f236ece5111a805072b38213f852ca4b62c5f8a4ec5ad343"},
+    {file = "spectrum_fundamentals-0.5.2-py3-none-any.whl", hash = "sha256:358235daa5ff48aa99437be238fa3da97b04cdd11e9feacedc3264f41661089e"},
+    {file = "spectrum_fundamentals-0.5.2.tar.gz", hash = "sha256:99fcde6f8e01f8647413eff0b9da64a0b6ea87a9a69a9ee96c1f2ffb76ec637f"},
 ]
 
 [package.dependencies]
@@ -3249,43 +3033,6 @@ files = [
 [package.dependencies]
 pbr = ">=2.0.0,<2.1.0 || >2.1.0"
 
-[[package]]
-name = "tables"
-version = "3.8.0"
-description = "Hierarchical datasets for Python"
-optional = false
-python-versions = ">=3.8"
-files = [
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-    {file = "tables-3.8.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:db185d855afd45a7259ddd0b53e5f2f8993bb134b370002c6c19532f27ce92ac"},
-    {file = "tables-3.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:70a3585a268beee6d0e71bfc9abec98da84d168182f350a2ffa1ae5e42798c18"},
-    {file = "tables-3.8.0-cp310-cp310-win_amd64.whl", hash = "sha256:117cf0f73ee2a5cba5c2b04e4aca375779aec66045aa63128e043dc608f2023b"},
-    {file = "tables-3.8.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:2861cd3ef9eb95eead7530e4de49fd130954871e7e6d2e288012797cb9d7c2e8"},
-    {file = "tables-3.8.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7e9bdbfbe025b6c751976382123c5f5cbd8fab6956aed776b0e8c889669e90d3"},
-    {file = "tables-3.8.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0821007048f2af8c1a21eb3d832072046c5df366e39587a7c7e4afad14e73fc"},
-    {file = "tables-3.8.0-cp311-cp311-win_amd64.whl", hash = "sha256:b9370c2a4dc0051aad6b71de4f1f9b0b8b60d30b662df5c742434f2b5c6a005e"},
-    {file = "tables-3.8.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:e19686fad4e8f5a91c3dc1eb4b7ea928838e86fefa474c63c5787a125ea79fc7"},
-    {file = "tables-3.8.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:239f15fa9881c257b5c0d9fb4cb8832778af1c5c8c1db6f6722466f8f26541e2"},
-    {file = "tables-3.8.0-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c83a74cac3c0629a0e83570d465f88843ef3609ef56a8ef9a49ee85ab3b8f02f"},
-    {file = "tables-3.8.0-cp38-cp38-win_amd64.whl", hash = "sha256:a5ccb80651c5fad6ac744e2a756b28cfac78eab3b8503f4a2320ee6653b3bee9"},
-    {file = "tables-3.8.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3375bfafc6cf305d13617a572ab3fffc51fae2fbe0f6efce9407a41f79970b62"},
-    {file = "tables-3.8.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:254a4d5c2009c7ebe4293b02b8d91ea60837bff85a3c0a40cd075b8f12b1e6c3"},
-    {file = "tables-3.8.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:da3c96456c473fb977cf6dbca9e889710ac020df1fa5b9ebb7f676e83996337d"},
-    {file = "tables-3.8.0-cp39-cp39-win_amd64.whl", hash = "sha256:72da9404094ef8277bf62fce8873e8dc141cee9a8763ec8e7080b2d0de206094"},
-    {file = "tables-3.8.0.tar.gz", hash = "sha256:34f3fa2366ce20b18f1df573a77c1d27306ce1f2a41d9f9eff621b5192ea8788"},
-]
-
-[package.dependencies]
-blosc2 = ">=2.0.0,<2.1.0"
-cython = ">=0.29.21"
-numexpr = ">=2.6.2"
-numpy = ">=1.19.0"
-packaging = "*"
-py-cpuinfo = "*"
-
-[package.extras]
-doc = ["ipython", "numpydoc", "sphinx (>=1.1)", "sphinx-rtd-theme"]
-
 [[package]]
 name = "threadpoolctl"
 version = "3.4.0"
@@ -3460,13 +3207,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.25.1"
+version = "20.26.0"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "virtualenv-20.25.1-py3-none-any.whl", hash = "sha256:961c026ac520bac5f69acb8ea063e8a4f071bcc9457b9c1f28f6b085c511583a"},
-    {file = "virtualenv-20.25.1.tar.gz", hash = "sha256:e08e13ecdca7a0bd53798f356d5831434afa5b07b93f0abdf0797b7a06ffe197"},
+    {file = "virtualenv-20.26.0-py3-none-any.whl", hash = "sha256:0846377ea76e818daaa3e00a4365c018bc3ac9760cbb3544de542885aad61fb3"},
+    {file = "virtualenv-20.26.0.tar.gz", hash = "sha256:ec25a9671a5102c8d2657f62792a27b48f016664c6873f6beed3800008577210"},
 ]
 
 [package.dependencies]
@@ -3475,7 +3222,7 @@ filelock = ">=3.12.2,<4"
 platformdirs = ">=3.9.1,<5"
 
 [package.extras]
-docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
+docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"]
 test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"]
 
 [[package]]
@@ -3523,4 +3270,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.0,<3.11.0"
-content-hash = "7d18a90e30d5a0227f0fe3c9658df405fac79e2cbc993515addb53a48d52abbc"
+content-hash = "8b8fff799603c037760578a6d90143064efc9d63d429f7f322d850525439a558"
diff --git a/pyproject.toml b/pyproject.toml
index 6299723..1558405 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -29,8 +29,7 @@ h5py = "^3.1.0"
 pymzml = "^2.5.0"
 pyteomics = "^4.3.3"
 lxml= '^4.5.2'
-tables = "^3.6.1"
-spectrum-fundamentals = ">=0.5.1,<0.6.0"
+spectrum-fundamentals = ">=0.5.2,<0.6.0"
 alphatims = "^1.0.8"
 sortedcontainers = "^2.4.0"
 
diff --git a/requirements.txt b/requirements.txt
index dec0b01..6342d52 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,12 +1,10 @@
 alphatims==1.0.8 ; python_version >= "3.8" and python_full_version < "3.11.0"
-blosc2==2.0.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 click==8.1.7 ; python_version >= "3.8" and python_full_version < "3.11.0"
 colorama==0.4.6 ; python_version >= "3.8" and python_full_version < "3.11.0" and platform_system == "Windows"
 contourpy==1.1.1 ; python_version >= "3.8" and python_full_version < "3.11.0"
 cycler==0.12.1 ; python_version >= "3.8" and python_full_version < "3.11.0"
-cython==3.0.10 ; python_version >= "3.8" and python_full_version < "3.11.0"
 fonttools==4.51.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
-h5py==3.10.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
+h5py==3.11.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 importlib-metadata==7.1.0 ; python_version >= "3.8" and python_version < "3.9"
 importlib-resources==6.4.0 ; python_version >= "3.8" and python_version < "3.10"
 joblib==1.4.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
@@ -17,31 +15,27 @@ markdown-it-py==3.0.0 ; python_version >= "3.8" and python_full_version < "3.11.
 matplotlib==3.7.5 ; python_version >= "3.8" and python_full_version < "3.11.0"
 mdurl==0.1.2 ; python_version >= "3.8" and python_full_version < "3.11.0"
 moepy==1.1.4 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
-msgpack==1.0.8 ; python_version >= "3.8" and python_full_version < "3.11.0"
 numba==0.58.1 ; python_version >= "3.8" and python_full_version < "3.11.0"
-numexpr==2.8.6 ; python_version >= "3.8" and python_full_version < "3.11.0"
 numpy==1.24.4 ; python_version >= "3.8" and python_full_version < "3.11.0"
 packaging==24.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 pandas==1.5.3 ; python_version >= "3.8" and python_full_version < "3.11.0"
 pillow==10.3.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 psutil==5.9.8 ; python_version >= "3.8" and python_full_version < "3.11.0"
-py-cpuinfo==9.0.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 pygments==2.17.2 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
-pymzml==2.5.6 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
+pymzml==2.5.9 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 pyparsing==3.1.2 ; python_version >= "3.8" and python_full_version < "3.11.0"
-pyteomics==4.7.1 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
+pyteomics==4.7.2 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 python-dateutil==2.9.0.post0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 pytz==2024.1 ; python_version >= "3.8" and python_full_version < "3.11.0"
 pyyaml==6.0.1 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 pyzstd==0.15.10 ; python_version >= "3.8" and python_full_version < "3.11.0"
-regex==2023.12.25 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
+regex==2024.4.16 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 rich==13.7.1 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 scikit-learn==1.3.2 ; python_version >= "3.8" and python_full_version < "3.11.0"
 scipy==1.10.1 ; python_version >= "3.8" and python_full_version < "3.11.0"
 six==1.16.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 sortedcontainers==2.4.0 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
-spectrum-fundamentals==0.5.0 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
-tables==3.8.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
+spectrum-fundamentals==0.5.2 ; python_full_version >= "3.8.0" and python_full_version < "3.11.0"
 threadpoolctl==3.4.0 ; python_version >= "3.8" and python_full_version < "3.11.0"
 tqdm==4.66.2 ; python_version >= "3.8" and python_full_version < "3.11.0"
 typing-extensions==4.11.0 ; python_version >= "3.8" and python_version < "3.9"
diff --git a/spectrum_io/spectral_library/dlib.py b/spectrum_io/spectral_library/dlib.py
index fe30db0..3abf10d 100644
--- a/spectrum_io/spectral_library/dlib.py
+++ b/spectrum_io/spectral_library/dlib.py
@@ -1,7 +1,7 @@
 import sqlite3
 import zlib
 from pathlib import Path
-from typing import List, Optional, Union
+from typing import IO, Dict, Union
 
 import numpy as np
 import pandas as pd
@@ -26,7 +26,16 @@
 class DLib(SpectralLibrary):
     """Main to init a DLib obj."""
 
-    def _calculate_masked_values(self, fragmentmz: List[np.ndarray], intensities: List[np.ndarray]):
+    def _initialize(self, out: Union[IO, sqlite3.Connection]):
+        if isinstance(out, IO):
+            raise TypeError("Not supported. Use msp/spectronaut if you want to write a text file.")
+        if self.mode == "w":
+            DLib._create_database(out)
+
+    def _get_handle(self):
+        return sqlite3.connect(self.out_path)
+
+    def _calculate_masked_values(self, fragmentmz: np.ndarray, intensities: np.ndarray):
         """
         Internal function that masks, filters, byte encodes, swaps and compresses fragmentmz \
         and intensities.
@@ -44,9 +53,10 @@ def _calculate_masked_values(self, fragmentmz: List[np.ndarray], intensities: Li
         i_bytes_list = []
         mz_lengths = []
         i_lengths = []
-        for mz, i in zip(fragmentmz, intensities):
+
+        full_mask = self._fragment_filter_passed(fragmentmz, intensities)
+        for mz, i, mask in zip(fragmentmz, intensities, np.array(full_mask)):
             # mask to only existing peaks
-            mask = i >= self.min_intensity_threshold
             sort_index = np.argsort(mz[mask])
             masked_mz_ordered = mz[mask][sort_index]
             masked_i_ordered = i[mask][sort_index]
@@ -59,50 +69,54 @@ def _calculate_masked_values(self, fragmentmz: List[np.ndarray], intensities: Li
             bytes_mz = bytes(masked_mz_ordered)
             bytes_i = bytes(masked_i_ordered)
             mz_bytes_list.append(zlib.compress(bytes_mz))
-            i_bytes_list.append(zlib.compress(bytes(bytes_i)))
+            i_bytes_list.append(zlib.compress(bytes_i))
             mz_lengths.append(len(bytes_mz))
             i_lengths.append(len(bytes_i))
         return mz_bytes_list, i_bytes_list, mz_lengths, i_lengths
 
     @staticmethod
-    def create_database(path: Union[str, Path]):
+    def _create_database(conn: sqlite3.Connection):
         """
         Creates the database file with prefab tables entries, peptidetoprotein (p2p) and metadata, according to the \
         dlib specification.
 
-        :param path: specifies the path of the created database file
+        :param conn: specifies the path of the created database file
         """
         sql_create_entries = """
-            CREATE TABLE entries
-            (   PrecursorMz double not null,
-                PrecursorCharge int not null,
-                PeptideModSeq string not null,
-                PeptideSeq string not null,
-                Copies int not null,
-                RTInSeconds double not null,
-                Score double not null,
-                MassEncodedLength int not null,
-                MassArray blob not null,
-                IntensityEncodedLength int not null,
-                IntensityArray blob not null,
-                CorrelationEncodedLength int,
-                CorrelationArray blob,
-                RTInSecondsStart double,
-                RTInSecondsStop double,
-                MedianChromatogramEncodedLength int,
-                MedianChromatogramArray blob,
-                SourceFile string not null
+            CREATE TABLE IF NOT EXISTS entries
+            (
+                PrecursorMz REAL NOT NULL,
+                PrecursorCharge INTEGER NOT NULL,
+                PeptideModSeq TEXT NOT NULL,
+                PeptideSeq TEXT NOT NULL,
+                Copies INTEGER NOT NULL DEFAULT 1,
+                RTInSeconds REAL NUT NULL,
+                Score REAL NOT NULL DEFAULT 0,
+                MassEncodedLength INTEGER NOT NULL,
+                MassArray BLOB NOT NULL,
+                IntensityEncodedLength INTEGER NOT NULL,
+                IntensityArray BLOB NOT NULL,
+                CorrelationEncodedLength INTEGER,
+                CorrelationArray BLOB,
+                RTInSecondsStart REAL,
+                RTInSecondsStop REAL,
+                MedianChromatogramEncodedLength INTEGER,
+                MedianChromatogramArray BLOB,
+                SourceFile TEXT NOT NULL DEFAULT 'Oktoberfest'
             )
         """
         sql_create_p2p = """
-            CREATE TABLE peptidetoprotein
-            (PeptideSeq string not null, isDecoy boolean, ProteinAccession string not null)
+            CREATE TABLE IF NOT EXISTS peptidetoprotein
+            (
+                PeptideSeq TEXT NOT NULL,
+                isDecoy BOOL DEFAULT FALSE,
+                ProteinAccession TEXT NOT NULL DEFAULT 'UNKNOWN'
+            )
         """
         sql_create_meta = """
-            CREATE TABLE metadata (Key string not null, Value string not null)
+            CREATE TABLE IF NOT EXISTS metadata (Key string not null, Value string not null)
         """
         sql_insert_meta = "INSERT INTO metadata VALUES (?,?)"
-        conn = sqlite3.connect(path)
         c = conn.cursor()
         c.execute(sql_create_entries)
         c.execute(sql_create_p2p)
@@ -111,34 +125,38 @@ def create_database(path: Union[str, Path]):
         c.execute(sql_insert_meta, ["staleProteinMapping", "true"])
         conn.commit()
 
-    def write(self):
-        """Writes the entries ad p2p table to file."""
-        self._write_entries(index=False, if_exists="append", method="multi", chunksize=self.chunksize)
-        self._write_p2p(index=False, if_exists="append", method="multi", chunksize=self.chunksize)
+    def _write(self, out: Union[IO, sqlite3.Connection], data: Dict[str, np.ndarray], metadata: pd.DataFrame):
+        if isinstance(out, IO):
+            raise TypeError("Not supported. Use msp/spectronaut if you want to write a text file.")
+        seqs = metadata["SEQUENCE"]
+        modseqs = metadata["MODIFIED_SEQUENCE"]
+        mass_mod_sequences = internal_to_mod_mass(modseqs)
 
-    def _write_entries(self, *args, **kwargs):
-        """
-        Internal function to write the entries table.
+        p_charges = metadata["PRECURSOR_CHARGE"]
+        p_mzs = (metadata["MASS"] + (p_charges * PARTICLE_MASSES["PROTON"])) / p_charges
+        # ces = metadata["COLLISION_ENERGY"]
 
-        :param args: forwarded to pandas.to_sql
-        :param kwargs: forwarded to pandas.to_sql
-        """
-        conn = sqlite3.connect(self.out_path)
-        self.entries.to_sql(name="entries", con=conn, *args, **kwargs)
-        conn.commit()
+        # prepare spectra
+        irts = data["irt"][:, 0]  # should create a 1D view of the (n_peptides, 1) shaped array
+        f_mzss = data["mz"]
+        f_intss = data["intensities"]
+        # f_annotss = data["annotation"].astype("S", copy=False)
 
-    def _write_p2p(self, *args, **kwargs):
-        """
-        Internal function to write the p2p table.
+        masked_values = self._calculate_masked_values(f_mzss, f_intss)
 
-        :param args: forwarded to pandas.to_sql
-        :param kwargs: forwarded to pandas.to_sql
-        """
-        conn = sqlite3.connect(self.out_path)
-        self.p2p.to_sql(name="peptidetoprotein", con=conn, *args, **kwargs)
-        conn.commit()
+        data_list = [*masked_values, p_charges, mass_mod_sequences, seqs, irts, p_mzs]
+        entries = pd.DataFrame(dict(zip(DLIB_COL_NAMES, data_list)))
+        p2p = pd.DataFrame({"PeptideSeq": seqs})
+
+        out.execute("BEGIN")
+
+        entries.to_sql(index=False, name="entries", con=out, if_exists="append", method="multi")
+        p2p.to_sql(index=False, name="peptidetoprotein", con=out, if_exists="append", method="multi")
+
+        out.commit()
+        # conn.close()
 
-    def prepare_spectrum(self):
+        # def prepare_spectrum(self):
         """Converts grpc output and metadata dataframe into dlib format."""
         # precursor_mz: Union[List[float], np.ndarray],
         # precursor_charges: Union[List[int], np.ndarray],
@@ -147,37 +165,37 @@ def prepare_spectrum(self):
         # fragmentmz: List[np.ndarray],
         # intensities: List[np.ndarray],
 
-        intensities = self.grpc_output[list(self.grpc_output)[0]]["intensity"]
-        fragment_mz = self.grpc_output[list(self.grpc_output)[0]]["fragmentmz"]
+        # intensities = self.grpc_output[list(self.grpc_output)[0]]["intensity"]
+        # fragment_mz = self.grpc_output[list(self.grpc_output)[0]]["fragmentmz"]
         # annotation = self.grpc_output[list(self.grpc_output)[0]]["annotation"]
-        irt = self.grpc_output[list(self.grpc_output)[1]]
-        retention_times = irt.flatten()
-        modified_sequences = self.spectra_input["MODIFIED_SEQUENCE"]
+        # irt = self.grpc_output[list(self.grpc_output)[1]]
+        # retention_times = irt.flatten()
+        # modified_sequences = self.spectra_input["MODIFIED_SEQUENCE"]
 
-        precursor_charges = self.spectra_input["PRECURSOR_CHARGE"]
-        precursor_masses = self.spectra_input["MASS"]
-        precursor_mz = (precursor_masses + (precursor_charges * PARTICLE_MASSES["PROTON"])) / precursor_charges
+        # precursor_charges = self.spectra_input["PRECURSOR_CHARGE"]
+        # precursor_masses = self.spectra_input["MASS"]
+        # precursor_mz = (precursor_masses + (precursor_charges * PARTICLE_MASSES["PROTON"])) / precursor_charges
 
-        self.create_database(self.out_path)
+        # self.create_database(self.out_path)
 
         # gather all values for the entries table and create pandas DataFrame
-        masked_values = self._calculate_masked_values(fragment_mz, intensities)
-        mass_mod_sequences = internal_to_mod_mass(modified_sequences)
-        sequences = internal_without_mods(modified_sequences)
-        data_list = [*masked_values, precursor_charges, mass_mod_sequences, sequences, retention_times, precursor_mz]
-        self.entries = pd.DataFrame(dict(zip(DLIB_COL_NAMES, data_list)))
+        # masked_values = self._calculate_masked_values(fragment_mz, intensities)
+        # mass_mod_sequences = internal_to_mod_mass(modified_sequences)
+        # sequences = internal_without_mods(modified_sequences)
+        # data_list = [*masked_values, precursor_charges, mass_mod_sequences, sequences, retention_times, precursor_mz]
+        # self.entries = pd.DataFrame(dict(zip(DLIB_COL_NAMES, data_list)))
 
         # hardcoded entries that we currently not use.
         # Visit https://bitbucket.org/searleb/encyclopedia/wiki/EncyclopeDIA%20File%20Formats for dlib specs
-        self.entries["Copies"] = 1  # this is hardcorded for now and unused
-        self.entries["Score"] = 0
-        self.entries["CorrelationEncodedLength"] = None
-        self.entries["CorrelationArray"] = None
-        self.entries["RTInSecondsStart"] = None
-        self.entries["RTInSecondsStop"] = None
-        self.entries["MedianChromatogramEncodedLength"] = None
-        self.entries["MedianChromatogramArray"] = None
-        self.entries["SourceFile"] = "Prosit"
+        # self.entries["Copies"] = 1  # this is hardcorded for now and unused
+        # self.entries["Score"] = 0
+        # self.entries["CorrelationEncodedLength"] = None
+        # self.entries["CorrelationArray"] = None
+        # self.entries["RTInSecondsStart"] = None
+        # self.entries["RTInSecondsStop"] = None
+        # self.entries["MedianChromatogramEncodedLength"] = None
+        # self.entries["MedianChromatogramArray"] = None
+        # self.entries["SourceFile"] = "Prosit"
 
         # gather all values for the p2p table and create pandas DataFrame
-        self.p2p = pd.DataFrame({"PeptideSeq": sequences, "isDecoy": False, "ProteinAccession": "unknown"})
+        # self.p2p = pd.DataFrame({"PeptideSeq": sequences, "isDecoy": False, "ProteinAccession": "unknown"})
diff --git a/spectrum_io/spectral_library/msp.py b/spectrum_io/spectral_library/msp.py
index 632b2d8..caad423 100644
--- a/spectrum_io/spectral_library/msp.py
+++ b/spectrum_io/spectral_library/msp.py
@@ -1,4 +1,5 @@
-from typing import IO, Dict
+from sqlite3 import Connection
+from typing import IO, Dict, Union
 
 import numpy as np
 import pandas as pd
@@ -16,8 +17,10 @@ def _assemble_fragment_string(f_mz: float, f_int: float, f_a: bytes):
         annot = f_a[:-2].decode() if f_a.endswith(b"1") else f_a.replace(b"+", b"^").decode()
         return f'{f_mz:.8f}\t{f_int:.4f}\t"{annot}/0.0ppm"\n'
 
-    def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
+    def _write(self, out: Union[IO, Connection], data: Dict[str, np.ndarray], metadata: pd.DataFrame):
         # prepare metadata
+        if isinstance(out, Connection):
+            raise TypeError("Not supported. Use DLib if you want to write a database file.")
         stripped_peptides = metadata["SEQUENCE"]
         modss = internal_to_mod_names(metadata["MODIFIED_SEQUENCE"])
         p_charges = metadata["PRECURSOR_CHARGE"]
@@ -50,5 +53,5 @@ def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
             lines.extend(fragment_list)
         out.writelines(lines)
 
-    def _write_header(self, out: IO):
+    def _initialize(self, out: Union[IO, Connection]):
         pass
diff --git a/spectrum_io/spectral_library/spectral_library.py b/spectrum_io/spectral_library/spectral_library.py
index 813df1e..1d8bbc9 100644
--- a/spectrum_io/spectral_library/spectral_library.py
+++ b/spectrum_io/spectral_library/spectral_library.py
@@ -2,6 +2,7 @@
 from multiprocessing import Queue
 from multiprocessing.managers import ValueProxy
 from pathlib import Path
+from sqlite3 import Connection
 from typing import IO, Dict, Optional, Union
 
 import numpy as np
@@ -44,10 +45,13 @@ def write(self, *args, **kwargs):
         :param args: Positional arguments to be passed to the internal _write method.
         :param kwargs: Keyword arguments to be passed to the internal _write method.
         """
-        with open(self.out_path, self.mode) as out:
-            self._write_header(out)
+        with self._get_handle() as out:
+            self._initialize(out)
             self._write(out, *args, **kwargs)
 
+    def _get_handle(self):
+        return open(self.out_path, self.mode)
+
     def async_write(self, queue: Queue, progress: ValueProxy):
         """
         Asynchronously write content to the output file from a queue.
@@ -55,8 +59,8 @@ def async_write(self, queue: Queue, progress: ValueProxy):
         :param queue: A queue from which content will be retrieved for writing.
         :param progress: An integer value representing the progress of the writing process.
         """
-        with open(self.out_path, self.mode) as out:
-            self._write_header(out)
+        with self._get_handle() as out:
+            self._initialize(out)
             while True:
                 content = queue.get()
                 if content is None:
@@ -82,7 +86,7 @@ def _fragment_filter_passed(
         return (f_mz != -1) & (f_int >= self.min_intensity_threshold)
 
     @abstractmethod
-    def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
+    def _write(self, out: Union[IO, Connection], data: Dict[str, np.ndarray], metadata: pd.DataFrame):
         """
         Internal writer function.
 
@@ -97,10 +101,5 @@ def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
         pass
 
     @abstractmethod
-    def _write_header(self, out: IO):
-        pass
-
-    @abstractmethod
-    def prepare_spectrum(self):
-        """Prepare spectrum."""
+    def _initialize(self, out: Union[IO, Connection]):
         pass
diff --git a/spectrum_io/spectral_library/spectronaut.py b/spectrum_io/spectral_library/spectronaut.py
index 2af0fd3..d249acc 100644
--- a/spectrum_io/spectral_library/spectronaut.py
+++ b/spectrum_io/spectral_library/spectronaut.py
@@ -1,7 +1,8 @@
 import os
 import re
 from itertools import chain, cycle
-from typing import IO, Dict, Tuple
+from sqlite3 import Connection
+from typing import IO, Dict, Tuple, Union
 
 import numpy as np
 import pandas as pd
@@ -25,8 +26,10 @@ def _assemble_fragment_string(f_int: float, f_mz: float, f_annot: bytes):
             f"{f_int:.4f},{f_mz:.8f},{m.group(2)},{m.group(1)},{m.group(3)},{m.group(4) if m.group(4) else 'noloss'}\n"
         )
 
-    def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
+    def _write(self, out: Union[IO, Connection], data: Dict[str, np.ndarray], metadata: pd.DataFrame):
         # prepare metadata
+        if isinstance(out, Connection):
+            raise TypeError("Not supported. Use DLib if you want to write a database file.")
         seqs = metadata["SEQUENCE"]
         modseqs = internal_to_spectronaut(metadata["MODIFIED_SEQUENCE"].apply(lambda x: "_" + x + "_"))
         p_charges = metadata["PRECURSOR_CHARGE"]
@@ -49,7 +52,9 @@ def _write(self, out: IO, data: Dict[str, np.ndarray], metadata: pd.DataFrame):
             fragment_list = vec_assemble(f_ints[cond], f_mzs[cond], f_annots[cond])
             out.writelines(chain.from_iterable(zip(cycle(line_start), fragment_list)))
 
-    def _write_header(self, out: IO):
+    def _initialize(self, out: Union[IO, Connection]):
+        if isinstance(out, Connection):
+            raise TypeError("Not supported. Use DLib if you want to write a database file.")
         if self.mode == "w":
             out.write(
                 "ModifiedPeptide,LabeledPeptide,StrippedPeptide,PrecursorCharge,PrecursorMz,iRT,CollisionEnergy,"
diff --git a/tests/unit_tests/test_spectral_library.py b/tests/unit_tests/test_spectral_library.py
index 2ca2ea4..7c90f1a 100644
--- a/tests/unit_tests/test_spectral_library.py
+++ b/tests/unit_tests/test_spectral_library.py
@@ -1,16 +1,17 @@
+import sqlite3
 from pathlib import Path
 
 import numpy as np
 import pandas as pd
 import pytest
 
-from spectrum_io.spectral_library import MSP, Spectronaut
+from spectrum_io.spectral_library import MSP, DLib, Spectronaut
 
 
 class TestMSP:
     """Class to test msp."""
 
-    def test_write(self, spectra_input, data, metadata):
+    def test_write(self, data, metadata):
         """Test write to file."""
         out_file = Path(__file__).parent / "test.msp"
         msp_lib = MSP(out_file)
@@ -43,7 +44,7 @@ def test_write(self, spectra_input, data, metadata):
 class TestSpectronaut:
     """Class to test msp."""
 
-    def test_write(self, spectra_input, data, metadata):
+    def test_write(self, data, metadata):
         """Test write to file."""
         out_file = Path(__file__).parent / "test.csv"
         msp_lib = Spectronaut(out_file)
@@ -68,16 +69,61 @@ def test_write(self, spectra_input, data, metadata):
         out_file.unlink()
 
 
-@pytest.fixture
-def spectra_input():
-    """Test spectra input."""
-    spectra_input = pd.DataFrame()
-    spectra_input["MODIFIED_SEQUENCE_SPEC"] = ["AAACCCC", "AAACILK"]
-    spectra_input["MODIFIED_SEQUENCE"] = ["AAAC[UNIMOD:4]CC[UNIMOD:4]CKR", "AAACILKKR"]
-    spectra_input["MASS"] = [123.4, 3232.1]
-    spectra_input["COLLISION_ENERGY"] = [10.0, 20.0]
-    spectra_input["PRECURSOR_CHARGE"] = [1, 2]
-    return spectra_input
+class TestDLib:
+    """Class to test DLib."""
+
+    def test_write(self, data, metadata):
+        """Test write to dlib library file."""
+        out_file = Path(__file__).parent / "test.dlib"
+        dlib = DLib(out_file)
+        dlib.write(data, metadata)
+        con = sqlite3.connect(out_file)
+        df_entries = pd.read_sql_query("SELECT * from entries", con)
+        df_p2p = pd.read_sql_query("SELECT * from peptidetoprotein", con)
+        df_meta = pd.read_sql_query("SELECT * from metadata", con)
+
+        con.close()
+
+        df_expected_entries = pd.DataFrame(
+            {
+                "PrecursorMz": [124.407276467, 1617.057276467],
+                "PrecursorCharge": [1, 2],
+                "PeptideModSeq": ["AAAC[+57.021464]CC[+57.021464]CKR", "AAACILKKR"],
+                "PeptideSeq": ["AAACCCCKR", "AAACILKKR"],
+                "Copies": 1,
+                "RTInSeconds": [982.12, 382.12],
+                "Score": 0.0,
+                "MassEncodedLength": [16, 24],
+                "MassArray": [
+                    b"x\x9c\xb3\xbfl\x0c\x06\xf6/g\x82\xc0,\x003\x01\x07\x04",
+                    b"x\x9c\xb3\xbfl\x0c\x06\xf67g\x82\xc0,\xfb\x07\x0c`\x00\x00rI\x08\x13",
+                ],
+                "IntensityEncodedLength": [8, 12],
+                "IntensityArray": [
+                    b"x\x9csZ\xc0\xc0\xe0\x08\xc4\x00\t\\\x01\xc4",
+                    b"x\x9c\xb3=s\xe6\xacS\x01\x03\x83\x93\x07\x03\x03\x00!\xd9\x03\xdf",
+                ],
+                "CorrelationEncodedLength": None,
+                "CorrelationArray": None,
+                "RTInSecondsStart": None,
+                "RTInSecondsStop": None,
+                "MedianChromatogramEncodedLength": None,
+                "MedianChromatogramArray": None,
+                "SourceFile": "Oktoberfest",
+            }
+        )
+
+        df_expected_p2p = pd.DataFrame(
+            {"PeptideSeq": ["AAACCCCKR", "AAACILKKR"], "isDecoy": 0, "ProteinAccession": "UNKNOWN"}
+        )
+
+        df_expected_meta = pd.DataFrame({"Key": ["version", "staleProteinMapping"], "Value": ["0.1.14", "true"]})
+
+        pd.testing.assert_frame_equal(df_expected_p2p, df_p2p)
+        pd.testing.assert_frame_equal(df_expected_entries, df_entries)
+        pd.testing.assert_frame_equal(df_expected_meta, df_meta)
+
+        out_file.unlink()
 
 
 @pytest.fixture