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  2. Google App Engine - Wikipedia

    en.wikipedia.org/wiki/Google_App_Engine

    Instead, one-to-many and many-to-many relationships can be accomplished using ReferenceProperty(). [11] Google Cloud Firestore is the successor to Google Cloud Datastore and replaces GQL with a document-based query method that treats stored objects as collections of documents. Firestore was launched in October 2017. [12]

  3. Data loading - Wikipedia

    en.wikipedia.org/wiki/Data_loading

    Full data refresh means that existing data in the target table is deleted first. All data from the source is then loaded into the target table, new indexes are created in the target table, and new measures are calculated for the updated table. Full refresh is easy to implement, but involves moving of much data which can take a long time, and ...

  4. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Relational databases are very well suited to flat data layouts, where relationships between data are only one or two levels deep. For example, an accounting database might need to look up all the line items for all the invoices for a given customer, a three-join query. Graph databases are aimed at datasets that contain many more links.

  5. Firebase - Wikipedia

    en.wikipedia.org/wiki/Firebase

    Firebase's first product was the Firebase Realtime Database, an API that synchronizes application data across iOS, Android, and Web devices, and stores it on Firebase's cloud. The product assists software developers in building real-time, collaborative applications.

  6. Hash table - Wikipedia

    en.wikipedia.org/wiki/Hash_table

    In a well-dimensioned hash table, the average time complexity for each lookup is independent of the number of elements stored in the table. Many hash table designs also allow arbitrary insertions and deletions of key–value pairs, at amortized constant average cost per operation. [3] [4] [5] Hashing is an example of a space-time tradeoff.

  7. MongoDB - Wikipedia

    en.wikipedia.org/wiki/MongoDB

    The user chooses a shard key, which determines how the data in a collection will be distributed. The data is split into ranges (based on the shard key) and distributed across multiple shards, which are masters with one or more replicas. Alternatively, the shard key can be hashed to map to a shard – enabling an even data distribution.

  8. NoSQL - Wikipedia

    en.wikipedia.org/wiki/NoSQL

    The key–value model is one of the simplest non-trivial data models, and richer data models are often implemented as an extension of it. The key–value model can be extended to a discretely ordered model that maintains keys in lexicographic order .

  9. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    A transactional table is the most basic and fundamental. The grain associated with a transactional fact table is usually specified as "one row per line in a transaction", e.g., every line on a receipt. Typically a transactional fact table holds data of the most detailed level, causing it to have a great number of dimensions associated with it.