arcticdb
ArcticDB DataFrame Database
Decision gist · record as of 2026-08-14
Yes, with conditions. Install if you need a versioned, time-series-optimized DataFrame database and can use S3 or LMDB storage. The active maintenance, wide platform support (Python 3.9–3.14), and zero known vulnerabilities are strong signals. However, production deployments require a paid license from ArcticDB Limited; confirm licensing terms with info@arcticdb.io before committing to production use. Medium install friction is acceptable for the capability gained.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- S3 or LMDB storage backend must be available; production use requires a paid license from ArcticDB Limited.
- Medium install friction due to compiled C++ components; prebuilt wheels available for Python 3.9–3.14 on Linux x86_64, Windows x86_64, and macOS arm64.
- Active maintenance with a release 4 days old and 2474 GitHub stars.
License · maintenance · safety
(unclear) — Business Source License 1.1 (BSL) — source is available but production use and Database Service deployments require a paid license from ArcticDB Limited. Current version converts to Apache 2.0 on Jul 27, 2028; contact info@arcticdb.io for commercial licensing.
last release 2026-08-10 (4 days) · last repo commit 2026-08-14 · 2,474 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 252,173 downloads/mo, #8,555 on PyPI
Alternatives
Verify before relying
pip install arcticdb
import arcticdb as adb
import pandas as pd
ac = adb.Arctic('lmdb:///')
lib = ac.create_library('my_lib')
lib.write('symbol', pd.DataFrame({'a': [1, 2, 3]}))
data = lib.read('symbol')- Performance benchmarks for billion-row time-series queries and compression ratios claimed in description.
- Specific latency and throughput characteristics for sparse data storage.
- Horizontal scaling behavior across symbols in production deployments.
What it is and what it does
ArcticDB is a Python-native database designed to store and query large Pandas DataFrames efficiently, backed by S3, LMDB, or Azure Blob Storage. It combines a Pandas-like API with a C++ data-processing engine to handle time-series data at scale, supporting versioning, snapshots, and schemaless updates without corrupting existing data. The package depends on pandas, numpy, attrs, protobuf, msgpack, pyyaml, packaging, and pytz.
It is built for scenarios where you need to persist and retrieve DataFrames with version history, efficiently index and filter time-series records, or stream sparse data without schema constraints. Data is pulled directly from storage to the client, eliminating a central server bottleneck. However, production deployments and Database Service use require a paid commercial license; the open-source BSL license permits evaluation and non-production use only.
Use it for
- Store and version-control multi-year financial time-series data (e.g., 20-year histories of 400,000+ securities) in a single symbol.
- Query and filter large DataFrames by time range or column values using Pandas-like syntax without loading entire datasets into memory.
- Create snapshots of DataFrame state at specific points in time and revert to previous versions for audit or analysis.
- Append and update sparse time-series data without enforcing a fixed schema across all records.
- Stream real-time data to S3 or LMDB with efficient compression and concurrent read access from multiple clients.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, with conditions.
Install if you need a versioned, time-series-optimized DataFrame database and can use S3 or LMDB storage. The active maintenance, wide platform support (Python 3.9–3.14), and zero known vulnerabilities are strong signals. However, production deployments require a paid license from ArcticDB Limited; confirm licensing terms with info@arcticdb.io before committing to production use. Medium install friction is acceptable for the capability gained.
Install
arcticdb on PyPI
Before you install
Medium install friction due to compiled C++ components; prebuilt wheels available for Python 3.9–3.14 on Linux x86_64, Windows x86_64, and macOS arm64. Active maintenance with a release 4 days old and 2474 GitHub stars.
S3 or LMDB storage backend must be available; production use requires a paid license from ArcticDB Limited.
License in practice
Business Source License 1.1 (BSL) — source is available but production use and Database Service deployments require a paid license from ArcticDB Limited. Current version converts to Apache 2.0 on Jul 27, 2028; contact info@arcticdb.io for commercial licensing.
Quickstart
pip install arcticdb
import arcticdb as adb
import pandas as pd
ac = adb.Arctic('lmdb:///')
lib = ac.create_library('my_lib')
lib.write('symbol', pd.DataFrame({'a': [1, 2, 3]}))
data = lib.read('symbol')Verify before relying
- Performance benchmarks for billion-row time-series queries and compression ratios claimed in description.
- Specific latency and throughput characteristics for sparse data storage.
- Horizontal scaling behavior across symbols in production deployments.
Package facts
| License | Not declared unclear |
| Python support | Not specified |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 8 packagespandasnumpyattrsprotobufmsgpackpyyamlpackagingpytz |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 252,173 / month, #8,555 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Operating System :: MacOSOperating System :: Microsoft :: WindowsOperating System :: POSIX :: LinuxProgramming Language :: Python :: 3Topic :: DatabaseTopic :: Database :: Database Engines/Servers |
Evidence: arcticdb-6.22.0-cp310-cp310-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp310-cp310-win_amd64.whl; arcticdb-6.22.0-cp311-cp311-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp311-cp311-win_amd64.whl; arcticdb-6.22.0-cp312-cp312-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp312-cp312-win_amd64.whl; arcticdb-6.22.0-cp313-cp313-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp313-cp313-win_amd64.whl; arcticdb-6.22.0-cp314-cp314-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp314-cp314-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp314-cp314-win_amd64.whl; arcticdb-6.22.0-cp39-cp39-macosx_15_0_arm64.whl; arcticdb-6.22.0-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.whl; arcticdb-6.22.0-cp39-cp39-win_amd64.whl
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