PostgreSQL vs. Hadoop vs. InfluxDB

I'm using PostgreSQL as the backend for my web applications. I like that I get the benefits of a SQL database while also being able to use features like HSTORE.

Primary DB

Postgres is the primary data store for Pathwright.

Used as the datastore for all of our Rails applications.

We use PostgreSQL to store most of our data.

Very simple and efficient database

PostgreSQL is our main data store for all relational data. It comes with a build in key-value store and integrates well with other areas of our platform.

RDBMS 가 필요한 경우 모두 postgresql 을 사용합니다. 신뢰성 있고, 안정적이며, 오픈소스입니다.

데이터베이스의 앞에는 pgbouncer 라는 connection pooler 를 사용합니다. 어플리케이션 서버에서 데이터베이스에 연결하는데 1ms 대가 소요됩니다.

Relational database for our business

database

PostgreSQL is our main datastore, and we make judicious use of its fantastic features: JSON columns, recursive CTEs, streaming binary replication, triggers, and constraints, among others.

Enterprise level database for all needs.

When we need to keep data in a safe place, we turn to PostgreSQL. Not only is the software rock-solid, but new versions add amazing features like JSON support that give us the best of both worlds: SQL and NoSQL.

5 years with PostgreSQL experience. 7 years of experience with MySQL and PostgreSQL combined.

PostgreSQL is the "pragmatic" choice, and, unsurprisingly, is serving us well!

Being a Django project, healthchecks.io also works with MySQL.

Storage for relational data

Backend database

Relational data storage

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

For our GIS data sets

High performance database for when performance really starts to matter.

I use this DB a lot, because is very stable.

PostgreSQL is our data store for both core clinical data, internal status and log data, as well as application-specific schemas for user-generated data.

General relational data for configuration and integration. Some reporting. Use as a better "mongo" for json document storage.

We use PostgreSQL for all transactional data storage where data must remain consistent at all times (not eventually consistent like document databases).

Database being used to store users data

PostgreSQL combines the best aspects of traditional SQL databases such as reliability, consistent performance, transactions, querying power, etc. with the flexibility of schemaless noSQL systems that are all the rage these days. Through the powerful JSON column types and indexes, you can now have your cake and eat it too! PostgreSQL may seem a bit arcane and old fashioned at first, but the developers have clearly shown that they understand databases and the storage trends better than almost anyone else. It definitely deserves to be part of everyone's toolbox; when you find yourself needing rock solid performance, operational simplicity and reliability, reach for PostgresQL.

My favorite SQL DB

Postgres is enlist's primary datastore.

Relational data.

One of the RDBMS that can be used for this CRUD module.

Backend for Drupal data, backend for weather forecast data using PostGIS on AWS RDS

Primary relational database which holds all schedules, customer information, ticket purchases, and transactions.

We needed a base for a data.

Store all of our match data as well as store hero statistics.

The main storage facility. It is performant enough and has the possibility to use NoSQL datatypes as well, it is also very good at development friendly and production enterprise quality and security

PostgreSQL is our datastore, used for long term storage and analytics. But not active data, such as messages enroute.

For Rails projects

relational database used for events/blog, sometimes more.

If a relational DBMS is required.

Data storage

we use postgres as our RDBMS

Stores data.

Performant database

All data is centrally kept in a PostgreSQL database. Part of the business logic is realized as PostgreSQL stored procedures. We make a lot of use of asynchronous notifications and other advanced PostgreSQL features.

We support PostgreSQL through our DSQL library.

Stores our data (artists, patrons, venues, etc)

PostgresSQL is our datastore of record. It is a flexible, poweful, relation datastore that fulfills so many needs.

Database

I use PostgreSQL due to its frequency of updates compared to MySQL, and based on preference. Nginx + PostgreSQL + Gunicorn is the best stack for running a Django based API.

django 프로젝트는 orm을 사용하기 때문에 DB를 변경하는것에 대한 두려움이 없습니다. 하지만 굳이 postgreSQL 을 사용한 것은 json 형식으로 저장이 가능하다는 점 때문입니다. 이것을 어떻게 사용할지는 아직 모르겠는것이 사실입니다.

하지만 restful api를 구축할때 이 부분에 대해 심도있게 다룰 예정입니다.

Database.

Base de datos de aplicación ITBID

(Ab)used for SQL + NoSQL.

Installed PostgreSQL server. Maintain database administration and database migration.

PostgreSQL is responsible for nearly all data storage, validation and integrity. We leverage constraints, functions and custom extensions to ensure we have only one source of truth for our data access rules and that those rules live as close to the data as possible. Call us crazy, but ORMs only lead to ruin and despair.

Postgres is used as the primary data store for users, checks, alerts and so on, as well as some aggregated stats.

For our persistent data storage needs, maps well with Django ORM

This is our single source of truth. Used with Django it is a perfect fit.

Heroku recommends PostgreSQL, so I use it and it seems to work well enough.

basic

We decided to go for Relational Database and PostgreSQL was the best fit (Search for custom fields etc).

Database layer for users, programs, and schedules

Can't beat PostgreSQL for relational data. User accounts, tokens, etc.

Our main database. Hosted on Bitnami in Google Compute Engine

we used postgres at talenthouse. some of the json stuff in there is pretty awesome. was quite fun using it with scala's slick.

We use postgresql for the merge between sql/nosql. A lot of our data is unstructured JSON, or JSON that is currently in flux due to some MVP/interation processes that are going on. PostgreSQL gives the capability to do this.

At the moment PostgreSQL on amazon is only at 9.5 which is one minor version down from support for document fragment updates which is something that we are waiting for. However, that may be some ways away.

Other than that, we are using PostgreSQL as our main SQL store as a replacement for all the MSSQL databases that we have. Not only does it have great support through RDS (small ops team), but it also has some great ways for us to migrate off RDS to managed EC2 instances down the line if we need to.

Used in great detail at Cloudfind. Profiled and improved bulk SQL upsert performance 200 fold.

Relational data stores solve a lot of problems reasonably well. Postgres has some data types that are really handy such as spatial, json, and a plethora of useful dates and integers. It has good availability of indexing solutions, and is well-supported for both custom modifications as well as hosting options (I like Amazon's Postgres for RDS). I use HoneySQL for Clojure as a composable AST that translates reliably to SQL. I typically use JDBC on Clojure, usually via org.clojure/java.jdbc.

Robust database

Reliable, mature and friendly database server with a great open source community.

One of our datasources for Ataccama ONE platform.

Backend database

Django Framework와 연동하여 사용하였습니다.

RDBM and Document storage combined with good performance makes this a must-have for HomeActions.

PostgreSQL is our go to database for storing primary data.

Tried MongoDB - early euphoria - later dread. Tried MySQL - not bad at all. Found PostgreSQL - will never go back. So much support for this it should be your first choice. Simple local (free) installation, and one-click setup in Heroku - lots of options in terms of pricing/performance combinations.

Postgres is our database of choice because of it's power and reliability. It is the storage backend of nearly all of our web applications.

Can be any database supported by "Peewee".

Scalable and high performance mixed-type storage. It is simply robust and met expectations

Great db, data storage.

a shared enterprise database on a server using schemas for isolation and built in random functionality

migrate the django model, also use pgcli

We use PostgreSQL as our source of truth and main data storage.

Store connectivity information and used by front-ends to query and display connected nodes

Default relational DB system used on most of KDL projects.

PostgreSQL is the default database for Gofus.

Developing programming skills.

I use PostgreSQL because it's fast, easy to use and works with every program we have.

Good clients in Python (Raspberry Pi) and R (RShiny), free PaaS available and sufficient for this project

• Database with Django's ORM
• Datastore for Worker Processes

Battle proven database for all the data

ACID compliant solid reliable storage with geospatial functions

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

大大大大大

Server and application metrics are all stored in InfluxDB for capacity planning and anomaly detection.

All our metrics go through InfluxDB, both applicative and system

To track time-series of course, utilizing few retention rules and continuous queries to keep time-series data fast and maintanable

InfluxDB ingests information from various sources (mostly Telegraf instances) into one place for monitoring purposes.

We use InfluxDB as a store for our data that gets fed into Grafana. It's ideal for this as it's a lightweight storage engine that can be modified on the fly by scripts without having to log into the server itself and manage tables. The HTTP API also makes it ideal for integrating with frontend services.