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Tag - ACID

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2014, Wednesday May 7

MongoDB + mORMot benchmark

Here are some benchmark charts about MongoDB integration in mORMot's ORM.

MongoDB appears as a serious competitor to SQL databases, with the potential benefit of horizontal scaling and installation/administration ease - performance is very high, and its document-based storage fits perfectly with mORMot's advanced ORM features like Shared nothing architecture (or sharding).

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MongoDB + mORMot ORM = ODM

MongoDB (from "humongous") is a cross-platform document-oriented database system, and certainly the best known NoSQL database.
According to http://db-engines.com in April 2014, MongoDB is in 5th place of the most popular types of database management systems, and first place for NoSQL database management systems.
Our mORMot gives premium access to this database, featuring full NoSQL and Object-Document Mapping (ODM) abilities to the framework.

Integration is made at two levels:

  • Direct low-level access to the MongoDB server, in the SynMongoDB.pas unit;
  • Close integration with our ORM (which becomes defacto an ODM), in the mORMotMongoDB.pas unit.

MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), which matches perfectly mORMot's RESTful approach.

This second article will focus on integration of MongoDB with our ORM.

Continue reading...

Direct MongoDB database access

MongoDB (from "humongous") is a cross-platform document-oriented database system, and certainly the best known NoSQL database.
According to http://db-engines.com in April 2014, MongoDB is in 5th place of the most popular types of database management systems, and first place for NoSQL database management systems.
Our mORMot framework gives premium access to this database, featuring full NoSQL and Object-Document Mapping (ODM) abilities to the framework.

Integration is made at two levels:

  • Direct low-level access to the MongoDB server, in the SynMongoDB.pas unit;
  • Close integration with our ORM (which becomes defacto an ODM), in the mORMotMongoDB.pas unit.

MongoDB eschews the traditional table-based relational database structure in favor of JSON-like documents with dynamic schemas (MongoDB calls the format BSON), which matches perfectly mORMot's RESTful approach.

In this first article, we will detail direct low-level access to the MongoDB server, via the SynMongoDB.pas unit.

Continue reading...

2014, Friday February 28

Are NoSQL databases ACID?

One of the main features you may miss when discovering NoSQL ("Not-Only SQL"?) databases, coming from a RDBMS background, is ACID.

ACID (Atomicity, Consistency, Isolation, Durability) is a set of properties that guarantee that database transactions are processed reliably. In the context of databases, a single logical operation on the data is called a transaction. For example, a transfer of funds from one bank account to another, even involving multiple changes such as debiting one account and crediting another, is a single transaction. (Wikipedia)

But are there any ACID NoSQL database?

Please ensure you read the Martin Fowler introduction about NoSQL databases.
And the corresponding video.

First of all, we can distinguish two types of NoSQL databases:

  1. Aggregate-oriented databases;
  2. Graph-oriented databases (e.g. Neo4J).

By design, most Graph-oriented databases are ACID!
This is a first good point.

Then, what about the other type?
In Aggregate-oriented databases, we can identify three sub-types:

  • Document-based NoSQL databases (e.g. MongoDB, CouchDB);
  • Key/Value NoSQL databases (e.g. Redis);
  • Column family NoSQL databases (e.g. Cassandra).
Whatever document/key/column oriented they are, they all use some kind of document storage.
It may be schema-less, blob-stored, column-driven, but it is always some set of values bound together to be persisted.
This set of values define a particular state of one entity, in a given model.
Which we may call Aggregate.

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