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Domains Document Store, Search, Timeseries; References to Cloud Tutor…
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# Document Store | ||
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Learn how to efficiently store JSON or other structured data, also nested, and | ||
how to query this data with ease, based on CrateDB's `OBJECT` data type. | ||
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Storing documents in CrateDB provides the same development convenience like the | ||
document-oriented storage layer of Lotus Notes / Domino, CouchDB, and MongoDB. | ||
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- [](inv:cloud#object) |
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# Full-Text Search | ||
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Learn how to set up your database for full-text search, how to create the | ||
relevant indices, and how to query your text data efficiently. A must-read | ||
for anyone looking to make sense of large volumes of unstructured text data. | ||
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- [](inv:cloud#full-text) | ||
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:::{note} | ||
CrateDB is an exceptional choice for handling complex queries and large-scale | ||
data sets. One of its standout features are its full-text search capabilities, | ||
built on top of the powerful Lucene library. This makes it a great fit for | ||
organizing, searching, and analyzing extensive datasets. | ||
::: |
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.. _timeseries-basics: | ||
.. _gen-ts: | ||
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========================= | ||
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# Time Series Data | ||
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Learn how to optimally use CrateDB within time series use-cases. | ||
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- [](#timeseries-basics) | ||
- [](#timeseries-normalize) | ||
- [Financial data collection and processing using pandas] | ||
- [](inv:cloud#time-series) | ||
- [](inv:cloud#time-series-advanced) | ||
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:::{toctree} | ||
:hidden: | ||
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generate/index | ||
normalize-intervals | ||
::: | ||
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[Financial data collection and processing using pandas]: https://community.crate.io/t/automating-financial-data-collection-and-storage-in-cratedb-with-python-and-pandas-2-0-0/916 |
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.. _timeseries-normalize: | ||
.. _normalize-intervals: | ||
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==================================== | ||
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