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ArcticDB
High-performance Python datastore for time series and tick data
What it is
A serverless DataFrame database built for the Python data science ecosystem, backed by a C++ data-processing and compression engine. It lets users read and write Pandas DataFrames, NumPy arrays, and native types to S3 or LMDB, with efficient indexing and querying of time-series data across billions of rows, versioning, snapshots, schemaless updates, and Pandas-like filtering and aggregation. Quant researchers and engineers working with large tick or time-series datasets in Python are its natural audience. Commercial use in production, including business environments or as a database service, requires a paid license from ArcticDB Limited.
At a glance
RecommendedOur rating, based on popularity, maintenance and how ready it is for real use.
| Best for | Professional quants |
|---|---|
| Used for | Data source, Data analysis |
| Markets | Multi-market |
| Stack | Python / C++ |
| Learning curve | Moderate learning curve |
| Practical value | High practical value |
| Cost | Free and open source |
| Hardware | No GPU needed |
| Maintenance | Commits today |
GitHub stars, last 30 days
Daily snapshots since 2026-09-12 (up to 30 days): +33 over the period, now 2,543. Gaps mean no snapshot was taken that day.
High performance datastore for time series and tick data.