CrateIO vs PostgreSQL

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CrateIO
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CrateIO vs PostgreSQL: What are the differences?

Developers describe CrateIO as "The Distributed Database for Docker". Crate is a distributed data store. Simply install Crate directly on your application servers and make the big centralized database a thing of the past. Crate takes care of synchronization, sharding, scaling, and replication even for mammoth data sets. On the other hand, PostgreSQL is detailed 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.

CrateIO and PostgreSQL belong to "Databases" category of the tech stack.

"Simplicity" is the primary reason why developers consider CrateIO over the competitors, whereas "Relational database" was stated as the key factor in picking PostgreSQL.

CrateIO and PostgreSQL are both open source tools. It seems that PostgreSQL with 5.44K GitHub stars and 1.8K forks on GitHub has more adoption than CrateIO with 2.49K GitHub stars and 333 GitHub forks.

What is CrateIO?

Crate is a distributed data store. Simply install Crate directly on your application servers and make the big centralized database a thing of the past. Crate takes care of synchronization, sharding, scaling, and replication even for mammoth data sets.

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 CrateIO and PostgreSQL?
      MySQL
      The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
      MongoDB
      MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
      Microsoft SQL Server
      Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
      MariaDB
      Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.
      SQLite
      SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
      See all alternatives
      Decisions about CrateIO and PostgreSQL
      Anton Sidelnikov
      Anton Sidelnikov
      Backend Developer at Beamery · | 5 upvotes · 9K views
      MongoDB
      MongoDB
      PostgreSQL
      PostgreSQL

      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
      Yonas Beshawred
      Yonas Beshawred
      CEO at StackShare · | 9 upvotes · 26.7K views
      atStackShareStackShare
      Memcached
      Memcached
      Heroku
      Heroku
      Amazon ElastiCache
      Amazon ElastiCache
      Rails
      Rails
      PostgreSQL
      PostgreSQL
      MemCachier
      MemCachier
      #Caching
      #RailsCaching

      We decided to use MemCachier as our Memcached provider because we were seeing some serious PostgreSQL performance issues with query-heavy pages on the site. We use MemCachier for all Rails caching and pretty aggressively too for the logged out experience (fully cached pages for the most part). We really need to move to Amazon ElastiCache as soon as possible so we can stop paying so much. The only reason we're not moving is because there are some restrictions on the network side due to our main app being hosted on Heroku.

      #Caching #RailsCaching

      See more
      John Kodumal
      John Kodumal
      CTO at LaunchDarkly · | 15 upvotes · 146.5K views
      atLaunchDarklyLaunchDarkly
      Kafka
      Kafka
      Amazon Kinesis
      Amazon Kinesis
      Redis
      Redis
      Amazon EC2
      Amazon EC2
      Amazon ElastiCache
      Amazon ElastiCache
      Consul
      Consul
      Patroni
      Patroni
      TimescaleDB
      TimescaleDB
      PostgreSQL
      PostgreSQL
      Amazon RDS
      Amazon RDS

      As we've evolved or added additional infrastructure to our stack, we've biased towards managed services. Most new backing stores are Amazon RDS instances now. We do use self-managed PostgreSQL with TimescaleDB for time-series data—this is made HA with the use of Patroni and Consul.

      We also use managed Amazon ElastiCache instances instead of spinning up Amazon EC2 instances to run Redis workloads, as well as shifting to Amazon Kinesis instead of Kafka.

      See more
      Joshua Dean Küpper
      Joshua Dean Küpper
      CEO at Scrayos UG (haftungsbeschränkt) · | 5 upvotes · 38.6K views
      atScrayos UG (haftungsbeschränkt)Scrayos UG (haftungsbeschränkt)
      Sentry
      Sentry
      GitLab
      GitLab
      PostgreSQL
      PostgreSQL
      MariaDB
      MariaDB

      We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and @Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQLs extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

      See more
      Alex A
      Alex A
      Founder at PRIZ Guru · | 6 upvotes · 8.4K views
      atPRIZ GuruPRIZ Guru
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL

      One of our battles at the very beginning of the road was choosing the right database. In fact, our first prototype was built on MySQL and back then nothing else was even under a consideration (don't ask me why). At some point, I was working on a project which was running on PostgreSQL and it is only then I understood the full power of it. We have over a billion of records in production instance, and we are able to optimize it to run fast and reliable. Well, now my default DB is PostgreSQL :)

      See more
      Tim Nolet
      Tim Nolet
      Founder, Engineer & Dishwasher at Checkly · | 8 upvotes · 61.6K views
      atChecklyHQChecklyHQ
      Amazon DynamoDB
      Amazon DynamoDB
      MongoDB
      MongoDB
      Node.js
      Node.js
      Heroku
      Heroku
      PostgreSQL
      PostgreSQL

      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 · 39.6K views
      atEnjoyHQEnjoyHQ
      PostgreSQL
      PostgreSQL
      MongoDB
      MongoDB
      RethinkDB
      RethinkDB

      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 · 10.6K views
      atYou Are My GUideYou Are My GUide
      MongoDB
      MongoDB
      TimescaleDB
      TimescaleDB
      PostgreSQL
      PostgreSQL

      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.

      See more
      Tor Hagemann
      Tor Hagemann
      at Socotra · | 2 upvotes · 2.2K views
      atSocotraSocotra
      Amazon DynamoDB
      Amazon DynamoDB
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL

      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!

      See more
      Joseph Irving
      Joseph Irving
      DevOps Engineer at uSwitch · | 8 upvotes · 7.4K views
      atuSwitchuSwitch
      Go
      Go
      PostgreSQL
      PostgreSQL
      MySQL
      MySQL
      Kubernetes
      Kubernetes
      Vault
      Vault

      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 · 23.4K views
      atThe Paperless ProjectThe Paperless Project
      PostgreSQL
      PostgreSQL
      SQLite
      SQLite

      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 · 169.2K views
      atCircleCICircleCI
      Amazon S3
      Amazon S3
      GitHub
      GitHub
      Redis
      Redis
      PostgreSQL
      PostgreSQL
      MongoDB
      MongoDB

      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 · | 10 upvotes · 15.5K views
      atIT MindsIT Minds
      AMP
      AMP
      PWA
      PWA
      React
      React
      MongoDB
      MongoDB
      Next.js
      Next.js
      GraphQL
      GraphQL
      Apollo
      Apollo
      PostgreSQL
      PostgreSQL
      TypeORM
      TypeORM
      Node.js
      Node.js
      TypeScript
      TypeScript
      #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
      MSSQL
      MSSQL
      PostgreSQL
      PostgreSQL
      AIOHTTP
      AIOHTTP
      asyncio
      asyncio
      Tornado
      Tornado

      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 · 17.9K views
      atAPX DevelopmentAPX Development
      PostgreSQL
      PostgreSQL
      MongoDB
      MongoDB
      Node.js
      Node.js
      Python
      Python

      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

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      Interest over time
      Reviews of CrateIO and PostgreSQL
      No reviews found
      How developers use CrateIO 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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