SQLite vs. Hadoop vs. RocksDB

Used for testing.

Used on our client(s)

Gestor de base de datos para el almacenamiento de datos en aplicaciones móviles.

For smaller internal tools we build that requires easy local storage.

There's really no call for something heavier for this site. SQLite is simple, easy to use and quite reliable given its age.

DB backend, when required

Local DB on iOS devices

For V.1.0 all data is stored using phonegap SqliteStorage plugin,

We support SQLite databases so that developers can interact with their data.

Storage of data for both mobile apps and native apps

All the dynamic data (i.e.: jobs) is stored in a simple SQLite database.

Все динамические данные (вакансии) хранятся в простой SQLite БД.

Database for mobile development

Local Django unit testing

We build queries in PHP with DSQL that work with SQLite. We also have SQLite data controller, so that you can build SQLite-based models.

Datasource for CoreData

Used SQLite with Ghost for Blogging service, both are free.

SQLite is used in the Android application, to store data on the mobile

basic

Only on local projects, nothing in production :-)

Inline DB on clients and apps.

RDBTools is a self-hosted application, and it is important that the installation process is simple. With SQLite, we create a new database file for every analysis. Once the analysis is done, the SQLite file can be thrown away easily.

Mobile app local databases.

For support reasons not relay used

The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...

The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.

in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).

YARN for cluster management

Product recommendations

• Raw storage engine
• Replication
• Fault-tolerance

Our data lake

Datalake and bigdata analytics

TBD. Good to have I think. Analytics on loads of data, recommendations?

Importing/Exporting data, interpreting results. Possible integration with SAS

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