Citus vs Oracle

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Citus
Citus

28
26
+ 1
8
Oracle
Oracle

846
616
+ 1
81
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Citus vs Oracle: What are the differences?

Citus: Worry-free Postgres for SaaS. Built to scale out. Citus is worry-free Postgres for SaaS. Made to scale out, Citus is an extension to Postgres that distributes queries across any number of servers. Citus is available as open source, as on-prem software, and as a fully-managed service; Oracle: An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism. Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.

Citus and Oracle belong to "Databases" category of the tech stack.

"Multi-core Parallel Processing" is the top reason why over 3 developers like Citus, while over 36 developers mention "Reliable" as the leading cause for choosing Oracle.

Citus is an open source tool with 3.64K GitHub stars and 273 GitHub forks. Here's a link to Citus's open source repository on GitHub.

- No public GitHub repository available -

What is Citus?

It's an extension to Postgres that distributes data and queries in a cluster of multiple machines. Its query engine parallelizes incoming SQL queries across these servers to enable human real-time (less than a second) responses on large datasets.

What is Oracle?

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
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    What are some alternatives to Citus and Oracle?
    CockroachDB
    Cockroach Labs is the company building CockroachDB, an open source, survivable, strongly consistent, scale-out SQL database.
    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.
    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.
    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.
    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.
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    Decisions about Citus and Oracle
    Dan Robinson
    Dan Robinson
    at Heap, Inc. · | 16 upvotes · 54.1K views
    atHeapHeap
    PostgreSQL
    PostgreSQL
    Citus
    Citus
    #DataStores
    #Databases

    PostgreSQL was an easy early decision for the founding team. The relational data model fit the types of analyses they would be doing: filtering, grouping, joining, etc., and it was the database they knew best.

    Shortly after adopting PG, they discovered Citus, which is a tool that makes it easy to distribute queries. Although it was a young project and a fork of Postgres at that point, Dan says the team was very available, highly expert, and it wouldn’t be very difficult to move back to PG if they needed to.

    The stuff they forked was in query execution. You could treat the worker nodes like regular PG instances. Citus also gave them a ton of flexibility to make queries fast, and again, they felt the data model was the best fit for their application.

    #DataStores #Databases

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    Dan Robinson
    Dan Robinson
    at Heap, Inc. · | 14 upvotes · 50.1K views
    atHeapHeap
    Heap
    Heap
    Citus
    Citus
    PostgreSQL
    PostgreSQL
    Kafka
    Kafka
    Node.js
    Node.js
    #MessageQueue
    #Databases
    #FrameworksFullStack

    At Heap, we searched for an existing tool that would allow us to express the full range of analyses we needed, index the event definitions that made up the analyses, and was a mature, natively distributed system.

    After coming up empty on this search, we decided to compromise on the “maturity” requirement and build our own distributed system around Citus and sharded PostgreSQL. It was at this point that we also introduced Kafka as a queueing layer between the Node.js application servers and Postgres.

    If we could go back in time, we probably would have started using Kafka on day one. One of the biggest benefits in adopting Kafka has been the peace of mind that it brings. In an analytics infrastructure, it’s often possible to make data ingestion idempotent.

    In Heap’s case, that means that, if anything downstream from Kafka goes down, we won’t lose any data – it’s just going to take a bit longer to get to its destination. We also learned that you want the path between data hitting your servers and your initial persistence layer (in this case, Kafka) to be as short and simple as possible, since that is the surface area where a failure means you can lose customer data. We learned that it’s a very good fit for an analytics tool, since you can handle a huge number of incoming writes with relatively low latency. Kafka also gives you the ability to “replay” the data flow: it’s like a commit log for your whole infrastructure.

    #MessageQueue #Databases #FrameworksFullStack

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    Interest over time
    Reviews of Citus and Oracle
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    How developers use Citus and Oracle
    Avatar of Onezino Gabriel
    Onezino Gabriel uses OracleOracle

    Gerenciamento de banco de dados utilizados por odos os serviços/aplicações criados

    Avatar of Adrian Harabulă
    Adrian Harabulă uses OracleOracle

    recommended solution at school, also used to try out alternatives to MySQL

    Avatar of Satoru Ishikawa
    Satoru Ishikawa uses OracleOracle

    データベース構成設計や実際のデータ操作など。実作業では9i, 10g, 11gを触った。

    Avatar of Hyunwoo Shim
    Hyunwoo Shim uses OracleOracle

    Oracle을 통해 RDB를 학습하였습니다.

    Avatar of douglasresende
    douglasresende uses OracleOracle

    I'm expert database.

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