PipelineDB vs PostgreSQL

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PipelineDB
PipelineDB

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PostgreSQL
PostgreSQL

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PostgreSQL vs PipelineDB: What are the differences?

Developers describe PostgreSQL as "A powerful, open source object-relational database system". PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions. On the other hand, PipelineDB is detailed as "The Streaming SQL Database". PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.

PostgreSQL and PipelineDB can be categorized as "Databases" tools.

PostgreSQL is an open source tool with 6.33K GitHub stars and 2.12K GitHub forks. Here's a link to PostgreSQL's open source repository on GitHub.

- No public GitHub repository available -

What is PipelineDB?

PipelineDB is an open-source relational database that runs SQL queries continuously on streams, incrementally storing results in tables.

What is PostgreSQL?

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
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      What are some alternatives to PipelineDB and PostgreSQL?
      TimescaleDB
      TimescaleDB: An open-source database built for analyzing time-series data with the power and convenience of SQL — on premise, at the edge, or in the cloud.
      Apache Spark
      Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
      RethinkDB
      RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.
      InfluxDB
      InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.
      Kafka
      Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
      See all alternatives
      Decisions about PipelineDB and PostgreSQL
      Anton Sidelnikov
      Anton Sidelnikov
      Backend Developer at Beamery · | 8 upvotes · 9.9K views
      PostgreSQL
      PostgreSQL
      MongoDB
      MongoDB

      In my opinion PostgreSQL is totally over MongoDB - not only works with structured data & SQL & strict types, but also has excellent support for unstructured data as separate data type (you can store arbitrary JSONs - and they may be also queryable, depending on one of format's you may choose). Both writes & reads are much faster, then in Mongo. So you can get best on Document NoSQL & SQL in single database..

      Formal downside of PostgreSQL is clustering scalability. There's not simple way to build distributed a cluster. However, two points:

      1) You will need much more time before you need to actually scale due to PG's efficiency. And if you follow database-per-service pattern, maybe you won't need ever, cause dealing few billion records on single machine is an option for PG.

      2) When you need to - you do it in a way you need, including as a part of app's logic (e.g. sharding by key, or PG-based clustering solution with strict model), scalability will be very transparent, much more obvious than Mongo's "cluster just works (but then fails)" replication.

      See more
      Tim Nolet
      Tim Nolet
      Founder, Engineer & Dishwasher at Checkly · | 8 upvotes · 77.8K views
      atChecklyHQChecklyHQ
      PostgreSQL
      PostgreSQL
      Heroku
      Heroku
      Node.js
      Node.js
      MongoDB
      MongoDB
      Amazon DynamoDB
      Amazon DynamoDB

      PostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

      When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

      In a nutshell:cPostgreSQL Heroku Node.js MongoDB Amazon DynamoDB

      When I started building Checkly, one of the first things on the agenda was how to actually structure our SaaS database model: think accounts, users, subscriptions etc. Weirdly, there is not a lot of information on this on the "blogopshere" (cringe...). After research and some false starts with MongoDB and Amazon DynamoDB we ended up with PostgreSQL and a schema consisting of just four tables that form the backbone of all generic "Saasy" stuff almost any B2B SaaS bumps into.

      In a nutshell:

      • We use Postgres on Heroku.
      • We use a "one database, on schema" approach for partitioning customer data.
      • We use an accounts, memberships and users table to create a many-to-many relation between users and accounts.
      • We completely decouple prices, payments and the exact ingredients for a customer's plan.

      All the details including a database schema diagram are in the linked blog post.

      See more
      Łukasz Korecki
      Łukasz Korecki
      CTO & Co-founder at EnjoyHQ · | 12 upvotes · 113.3K views
      atEnjoyHQEnjoyHQ
      RethinkDB
      RethinkDB
      MongoDB
      MongoDB
      PostgreSQL
      PostgreSQL

      We initially chose RethinkDB because of the schema-less document store features, and better durability resilience/story than MongoDB In the end, it didn't work out quite as we expected: there's plenty of scalability issues, it's near impossible to run analytical workloads and small community makes working with Rethink a challenge. We're in process of migrating all our workloads to PostgreSQL and hopefully, we will be able to decommission our RethinkDB deployment soon.

      See more
      Mauro Bennici
      Mauro Bennici
      CTO at You Are My GUide · | 7 upvotes · 28.7K views
      atYou Are My GUideYou Are My GUide
      PostgreSQL
      PostgreSQL
      TimescaleDB
      TimescaleDB
      MongoDB
      MongoDB

      PostgreSQL plus TimescaleDB allow us to concentrate the business effort on how to analyze valuable data instead of manage them on IT side. We are now able to ingest thousand of social shares "managed" data without compromise the scalability of the system or the time query. TimescaleDB is transparent to PostgreSQL , so we continue to use the same SQL syntax without any changes. At the same time, because we need to manage few document objects we dismissed the MongoDB cluster.

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      Tor Hagemann
      Tor Hagemann
      at Socotra · | 2 upvotes · 2.3K views
      atSocotraSocotra
      MySQL
      MySQL
      PostgreSQL
      PostgreSQL
      Amazon DynamoDB
      Amazon DynamoDB

      Much of our data model is relational, which makes MySQL or PostgreSQL (and family) fit the API's we need to build, in order to meet the needs of our customers.

      Sometimes the flexibility of a NoSQL store like Amazon DynamoDB is very useful, but the lack of consistency really impacts usability and performance long-term, compared with viable alternatives. At our current scale, we've seen huge benefits from moving some of our tables out of Dynamo and doing more in SQL.

      There will always be use cases for NoSQL and key-values stores, but if your model is well understood in your business/industry: relational databases are the way to go after finding product-market fit. Always understand the trade-offs (and a few intimate details) of any data store before you add to your company's stack!

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      Joseph Irving
      Joseph Irving
      DevOps Engineer at uSwitch · | 8 upvotes · 11.1K views
      atUswitchUswitch
      Vault
      Vault
      Kubernetes
      Kubernetes
      MySQL
      MySQL
      PostgreSQL
      PostgreSQL
      Go
      Go

      At uSwitch we use Vault to generate short lived database credentials for our applications running in Kubernetes. We wanted to move from an environment where we had 100 dbs with a variety of static passwords being shared around to a place where each pod would have credentials that only last for its lifetime.

      We chose vault because:

      • It had built in Kubernetes support so we could use service accounts to permission which pods could access which database.

      • A terraform provider so that we could configure both our RDS instances and their vault configuration in one place.

      • A variety of database providers including MySQL/PostgreSQL (our most common dbs).

      • A good api/Go -sdk so that we could build tooling around it to simplify development worfklow.

      • It had other features we would utilise such as PKI

      See more
      Daniel Quinn
      Daniel Quinn
      Senior Developer at Workfinder · | 2 upvotes · 117.6K views
      atThe Paperless ProjectThe Paperless Project
      SQLite
      SQLite
      PostgreSQL
      PostgreSQL

      SQLite is a tricky beast. It's great if you're working single-threaded, but a Terrible Idea if you've got more than one concurrent connection. You use it because it's easy to setup, light, and portable (it's just a file).

      In Paperless, we've built a self-hosted web application, so it makes sense to standardise on something small & light, and as we don't have to worry about multiple connections (it's just you using the app), it's a perfect fit.

      For users wanting to scale Paperless up to a multi-user environment though, we do provide the hooks to switch to PostgreSQL .

      See more
      Robert Zuber
      Robert Zuber
      CTO at CircleCI · | 22 upvotes · 718.4K views
      atCircleCICircleCI
      MongoDB
      MongoDB
      PostgreSQL
      PostgreSQL
      Redis
      Redis
      GitHub
      GitHub
      Amazon S3
      Amazon S3

      We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

      As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

      When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

      See more
      Martin Johannesson
      Martin Johannesson
      Senior Software Developer at IT Minds · | 11 upvotes · 37.3K views
      atIT MindsIT Minds
      TypeScript
      TypeScript
      Node.js
      Node.js
      TypeORM
      TypeORM
      PostgreSQL
      PostgreSQL
      Apollo
      Apollo
      GraphQL
      GraphQL
      Next.js
      Next.js
      MongoDB
      MongoDB
      React
      React
      PWA
      PWA
      AMP
      AMP
      #B2B
      #Backend
      #Serverless

      At IT Minds we create customized internal or #B2B web and mobile apps. I have a go to stack that I pitch to our customers consisting of 3 core areas. 1) A data core #backend . 2) A micro #serverless #backend. 3) A user client #frontend.

      For the Data Core I create a backend using TypeScript Node.js and with TypeORM connecting to a PostgreSQL Exposing an action based api with Apollo GraphQL

      For the micro serverless backend, which purpose is verification for authentication, autorization, logins and the likes. It is created with Next.js api pages. Using MongoDB to store essential information, caching etc.

      Finally the frontend is built with React using Next.js , TypeScript and @Apollo. We create the frontend as a PWA and have a AMP landing page by default.

      See more
      Jelena Dedovic
      Jelena Dedovic
      Software Engineer · | 5 upvotes · 97.6K views
      Tornado
      Tornado
      asyncio
      asyncio
      AIOHTTP
      AIOHTTP
      PostgreSQL
      PostgreSQL
      MSSQL
      MSSQL

      Investigating Tortoise ORM and GINO ORM...

      I need to introduce some async ORM with the current stack: Tornado with asyncio loop, AIOHTTP, with PostgreSQL and MSSQL. This project revolves heavily around realtime and due to the realtime requirements, blocking during database access is not acceptable.

      Considering that these ORMs are both young projects, I wondered if anybody had some experience with similar stack and these async ORMs?

      See more
      Nicolas Apx
      Nicolas Apx
      CEO - FullStack Javascript at Apx Development Limited · | 14 upvotes · 33.4K views
      atAPX DevelopmentAPX Development
      Python
      Python
      Node.js
      Node.js
      MongoDB
      MongoDB
      PostgreSQL
      PostgreSQL

      I am planning on building a micro-service eCommerce back-end to be easy to reuse in any project as we need. I would like to use both Python and Node.js and MongoDB & PostgreSQL , in your opinion which one would best suited for the following services:

      • Users-service
      • Products-service
      • Auth-service
      • Inventory-service
      • Order-service
      • Payment-service
      • Sku-service
      • And more not yet defined....

      Thanks

      Nicolas

      See more
      Ruby
      Ruby
      Rails
      Rails
      React
      React
      Redux
      Redux
      Create React App
      Create React App
      Jest
      Jest
      react-testing-library
      react-testing-library
      RSpec
      RSpec
      PostgreSQL
      PostgreSQL
      MongoDB
      MongoDB
      Redis
      Redis
      React Native
      React Native
      Next.js
      Next.js
      Python
      Python
      Bit
      Bit
      JavaScript
      JavaScript

      I'm working as one of the engineering leads in RunaHR. As our platform is a Saas, we thought It'd be good to have an API (We chose Ruby and Rails for this) and a SPA (built with React and Redux ) connected. We started the SPA with Create React App since It's pretty easy to start.

      We use Jest as the testing framework and react-testing-library to test React components. In Rails we make tests using RSpec.

      Our main database is PostgreSQL, but we also use MongoDB to store some type of data. We started to use Redis  for cache and other time sensitive operations.

      We have a couple of extra projects: One is an Employee app built with React Native and the other is an internal back office dashboard built with Next.js for the client and Python in the backend side.

      Since we have different frontend apps we have found useful to have Bit to document visual components and utils in JavaScript.

      See more
      George Krachtopoulos
      George Krachtopoulos
      GraphQL
      GraphQL
      MongoDB
      MongoDB
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL
      Node.js
      Node.js
      React
      React
      Django
      Django

      I would like to build a medium to large scale app, that has real-time operations and a good authentication system and a secure and fast API. Should I use Django with React only? Or maybe use Django for the API, Node.js for real-time operations and React for the frontend? Any suggestions? Which database should I use with those technologies? Should I use both MySQL / PostgreSQL and MongoDB together? Should I use only MongoDB or MySQL / PostgreSQL? Or is it better to go with both MySQL and PostgreSQL at the same time? Should I use also GraphQL?

      See more
      Erin G
      Erin G
      Linux
      Linux
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL
      Microsoft SQL Server
      Microsoft SQL Server

      I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

      1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
      2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
      See more
      George Krachtopoulos
      George Krachtopoulos
      GraphQL
      GraphQL
      React
      React
      Node.js
      Node.js
      MongoDB
      MongoDB
      Django
      Django
      Python
      Python
      PostgreSQL
      PostgreSQL

      Hello everyone,

      Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

      *The project is going to use React for the front-end and GraphQL is going to be used for the API.

      Thank you all. Any answer or advice would be really helpful!

      See more
      Interest over time
      Reviews of PipelineDB and PostgreSQL
      No reviews found
      How developers use PipelineDB and PostgreSQL
      Avatar of AngeloR
      AngeloR uses PostgreSQLPostgreSQL

      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.

      Avatar of Cloudcraft
      Cloudcraft uses PostgreSQLPostgreSQL

      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.

      Avatar of Brandon Adams
      Brandon Adams uses PostgreSQLPostgreSQL

      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.

      Avatar of ReviewTrackers
      ReviewTrackers uses PostgreSQLPostgreSQL

      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.

      Avatar of Jeff Flynn
      Jeff Flynn uses PostgreSQLPostgreSQL

      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.

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