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  2. Schema migration - Wikipedia

    en.wikipedia.org/wiki/Schema_migration

    Execute a backfill in the database: for all data that was written in the old format, move it over to the new format. Deploy an application change once more that stops reading the old data. Remove the old format data from the schema.

  3. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Cloud-based data warehouses like Amazon Redshift, Google BigQuery, Microsoft Azure Synapse Analytics and Snowflake Inc. have been able to provide highly scalable computing power. This lets businesses forgo preload transformations and replicate raw data into their data warehouses, where it can transform them as needed using SQL .

  4. Data migration - Wikipedia

    en.wikipedia.org/wiki/Data_migration

    Migration, which focuses on the digital object itself, is the act of transferring, or rewriting data from an out-of-date medium to a current medium and has for many years been considered the only viable approach to long-term preservation of digital objects. [10] Reproducing brittle newspapers onto microfilm is an example of such migration.

  5. Cosmos DB - Wikipedia

    en.wikipedia.org/wiki/Cosmos_DB

    The SQL API lets clients create, update and delete containers and items. Items can be queried with a read-only, JSON-friendly SQL dialect. [8] As Cosmos DB embeds a JavaScript engine, the SQL API also enables: Stored procedures. Functions that bundle an arbitrarily complex set of operations and logic into an ACID-compliant transaction. They are ...

  6. SQL - Wikipedia

    en.wikipedia.org/wiki/SQL

    SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...

  7. Data orientation - Wikipedia

    en.wikipedia.org/wiki/Data_orientation

    Tabular data is two dimensional — data is modeled as rows and columns. However, computer systems represent data in a linear memory model, both in-disk and in-memory. [7] [8] [9] Therefore, a table in a linear memory model requires mapping its two-dimensional scheme into a one-dimensional space.

  8. IBM Db2 - Wikipedia

    en.wikipedia.org/wiki/IBM_Db2

    In 2018, the IBM SQL product was renamed and is now known as IBM Db2 Big SQL (Big SQL). Big SQL is an enterprise-grade, hybrid ANSI-compliant SQL on the Hadoop engine delivering massively parallel processing (MPP) and advanced data query. Additional benefits include low latency, high performance, security, SQL compatibility and federation ...

  9. Bigtable - Wikipedia

    en.wikipedia.org/wiki/Bigtable

    Bigtable development began in 2004. [1] It is now used by a number of Google applications, such as Google Analytics, [2] web indexing, [3] MapReduce, which is often used for generating and modifying data stored in Bigtable, [4] Google Maps, [5] Google Books search, "My Search History", Google Earth, Blogger.com, Google Code hosting, YouTube, [6] and Gmail. [7]