Feature highlights¶

Important fundamental features of CrateDB.

Store JSON documents or other structured data, also nested, using CrateDB’s OBJECT and ARRAY container data types. Query this data with ease, fully indexed thus performant from the start, optionally using relational joins.

What’s inside: CrateDB can do the same like Lotus Notes / Domino, CouchDB, MongoDB, and PostgreSQL’s JSON data type.

Unified search:

Like Elasticsearch and Solr, CrateDB is based on Apache Lucene, the premier industry-grade full-text search engine library.

CrateDB offers native BM25 term search and vector search on large volumes of unstructured information, all using SQL. CrateDB enables you to build powerful full-text and semantic search experiences for websites, applications, and enterprise data.

What’s inside: Learn how to leverage full-text, geospatial-, vector-, and hybrid-search capabilities.

Advanced querying:

Mix full-text search with time series aspects, and run powerful aggregations or other kinds of complex queries on your data. CrateDB supports effective time series analysis with fast aggregations, relational features for JOIN operations, and a rich set of built-in functions.

What’s inside: Aggregations with gap filling / interpolation, common table expressions (CTEs), LAG / LEAD window functions, time bucketing, HyperLogLog, LOCF/NOCB, LTTB, UNNEST.

Related sections

Solutions and use cases:

Learn how to use CrateDB for time series use-cases, about industry solutions built with CrateDB and how others are using CrateDB successfully with both standard software components and in proprietary system landscapes.

What’s inside: Solutions built with CrateDB. Time series data. Industrial big data. Real-time raw-data analytics. Machine learning.

Categories / Topics:

Learn how to apply CrateDB’s features to optimally cover different application categories and topic domains. For example, connect CrateDB with third-party software applications, libraries, and frameworks.

What’s inside: Business intelligence, data lineage, data migrations, data visualization, programming frameworks, software testing.