Amazon RDS聽vs聽InfluxDB

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Amazon RDS
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Amazon RDS vs InfluxDB: What are the differences?

Developers describe Amazon RDS as "Set up, operate, and scale a relational database in the cloud". Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call. On the other hand, InfluxDB is detailed as "An open-source distributed time series database with no external dependencies". 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..

Amazon RDS belongs to "SQL Database as a Service" category of the tech stack, while InfluxDB can be primarily classified under "Databases".

Some of the features offered by Amazon RDS are:

  • Pre-configured Parameters
  • Monitoring and Metrics
  • Automatic Software Patching

On the other hand, InfluxDB provides the following key features:

  • Time-Centric Functions
  • Scalable Metrics
  • Events

"Reliable failovers" is the top reason why over 163 developers like Amazon RDS, while over 35 developers mention "Time-series data analysis" as the leading cause for choosing InfluxDB.

InfluxDB is an open source tool with 16.6K GitHub stars and 2.37K GitHub forks. Here's a link to InfluxDB's open source repository on GitHub.

According to the StackShare community, Amazon RDS has a broader approval, being mentioned in 1408 company stacks & 509 developers stacks; compared to InfluxDB, which is listed in 116 company stacks and 38 developer stacks.

- No public GitHub repository available -

What is Amazon RDS?

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

What is 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.
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    What are some alternatives to Amazon RDS and InfluxDB?
    Amazon Redshift
    It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.
    Apache Aurora
    Apache Aurora is a service scheduler that runs on top of Mesos, enabling you to run long-running services that take advantage of Mesos' scalability, fault-tolerance, and resource isolation.
    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.
    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.
    Heroku Postgres
    Heroku Postgres provides a SQL database-as-a-service that lets you focus on building your application instead of messing around with database management.
    See all alternatives
    Decisions about Amazon RDS and InfluxDB
    Tim Specht
    Tim Specht
    鈥嶤o-Founder and CTO at Dubsmash | 13 upvotes 57.5K views
    atDubsmashDubsmash
    Amazon RDS for Aurora
    Amazon RDS for Aurora
    Redis
    Redis
    Amazon DynamoDB
    Amazon DynamoDB
    Amazon RDS
    Amazon RDS
    Heroku
    Heroku
    PostgreSQL
    PostgreSQL
    #PlatformAsAService
    #Databases
    #NosqlDatabaseAsAService
    #SqlDatabaseAsAService

    Over the years we have added a wide variety of different storages to our stack including PostgreSQL (some hosted by Heroku, some by Amazon RDS) for storing relational data, Amazon DynamoDB to store non-relational data like recommendations & user connections, or Redis to hold pre-aggregated data to speed up API endpoints.

    Since we started running Postgres ourselves on RDS instead of only using the managed offerings of Heroku, we've gained additional flexibility in scaling our application while reducing costs at the same time.

    We are also heavily testing Amazon RDS for Aurora in its Postgres-compatible version and will also give the new release of Aurora Serverless a try!

    #SqlDatabaseAsAService #NosqlDatabaseAsAService #Databases #PlatformAsAService

    See more
    Julien DeFrance
    Julien DeFrance
    Principal Software Engineer at Tophatter | 16 upvotes 381.1K views
    atSmartZipSmartZip
    Amazon DynamoDB
    Amazon DynamoDB
    Ruby
    Ruby
    Node.js
    Node.js
    AWS Lambda
    AWS Lambda
    New Relic
    New Relic
    Amazon Elasticsearch Service
    Amazon Elasticsearch Service
    Elasticsearch
    Elasticsearch
    Superset
    Superset
    Amazon Quicksight
    Amazon Quicksight
    Amazon Redshift
    Amazon Redshift
    Zapier
    Zapier
    Segment
    Segment
    Amazon CloudFront
    Amazon CloudFront
    Memcached
    Memcached
    Amazon ElastiCache
    Amazon ElastiCache
    Amazon RDS for Aurora
    Amazon RDS for Aurora
    MySQL
    MySQL
    Amazon RDS
    Amazon RDS
    Amazon S3
    Amazon S3
    Docker
    Docker
    Capistrano
    Capistrano
    AWS Elastic Beanstalk
    AWS Elastic Beanstalk
    Rails API
    Rails API
    Rails
    Rails
    Algolia
    Algolia

    Back in 2014, I was given an opportunity to re-architect SmartZip Analytics platform, and flagship product: SmartTargeting. This is a SaaS software helping real estate professionals keeping up with their prospects and leads in a given neighborhood/territory, finding out (thanks to predictive analytics) who's the most likely to list/sell their home, and running cross-channel marketing automation against them: direct mail, online ads, email... The company also does provide Data APIs to Enterprise customers.

    I had inherited years and years of technical debt and I knew things had to change radically. The first enabler to this was to make use of the cloud and go with AWS, so we would stop re-inventing the wheel, and build around managed/scalable services.

    For the SaaS product, we kept on working with Rails as this was what my team had the most knowledge in. We've however broken up the monolith and decoupled the front-end application from the backend thanks to the use of Rails API so we'd get independently scalable micro-services from now on.

    Our various applications could now be deployed using AWS Elastic Beanstalk so we wouldn't waste any more efforts writing time-consuming Capistrano deployment scripts for instance. Combined with Docker so our application would run within its own container, independently from the underlying host configuration.

    Storage-wise, we went with Amazon S3 and ditched any pre-existing local or network storage people used to deal with in our legacy systems. On the database side: Amazon RDS / MySQL initially. Ultimately migrated to Amazon RDS for Aurora / MySQL when it got released. Once again, here you need a managed service your cloud provider handles for you.

    Future improvements / technology decisions included:

    Caching: Amazon ElastiCache / Memcached CDN: Amazon CloudFront Systems Integration: Segment / Zapier Data-warehousing: Amazon Redshift BI: Amazon Quicksight / Superset Search: Elasticsearch / Amazon Elasticsearch Service / Algolia Monitoring: New Relic

    As our usage grows, patterns changed, and/or our business needs evolved, my role as Engineering Manager then Director of Engineering was also to ensure my team kept on learning and innovating, while delivering on business value.

    One of these innovations was to get ourselves into Serverless : Adopting AWS Lambda was a big step forward. At the time, only available for Node.js (Not Ruby ) but a great way to handle cost efficiency, unpredictable traffic, sudden bursts of traffic... Ultimately you want the whole chain of services involved in a call to be serverless, and that's when we've started leveraging Amazon DynamoDB on these projects so they'd be fully scalable.

    See more
    Interest over time
    Reviews of Amazon RDS and InfluxDB
    Review ofInfluxDBInfluxDB

    Influx doesn't currently natively support horizontal distribution. Hard to recommend it until they implement that.

    Avatar of YaronWittenstein
    Computer Science
    Review ofInfluxDBInfluxDB

    InfluxDB is a game changer

    How developers use Amazon RDS and InfluxDB
    Avatar of Pathwright
    Pathwright uses Amazon RDSAmazon RDS

    While we initially started off running our own Postgres cluster, we evaluated RDS and found it to be an excellent fit for us.

    The failovers, manual scaling, replication, Postgres upgrades, and pretty much everything else has been super smooth and reliable.

    We'll probably need something a little more complex in the future, but RDS performs admirably for now.

    Avatar of AngeloR
    AngeloR uses Amazon RDSAmazon RDS

    We are using RDS for managing PostgreSQL and legacy MSSQL databases.

    Unfortunately while RDS works great for managing the PostgreSQL systems, MSSQL is very much a second class citizen and they don't offer very much capability. Infact, in order to upgrade instance storage for MSSQL we actually have to spin up a new cluster and migrate the data over.

    Avatar of ShadowICT
    ShadowICT uses InfluxDBInfluxDB

    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.

    Avatar of Goyoboard
    Goyoboard uses InfluxDBInfluxDB

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

    Avatar of Wirkn Inc.
    Wirkn Inc. uses Amazon RDSAmazon RDS

    Our PostgreSQL servers, where we keep the bulk of Wirkn data, are hosted on the fantastically easy and reliable AWS RDS platform.

    Avatar of Digital2Go
    Digital2Go uses Amazon RDSAmazon RDS

    We use Aurora for our OLTP database, it provides significant speed increases on top of MySQL without the need to manage it

    Avatar of sapslaj
    sapslaj uses InfluxDBInfluxDB

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

    Avatar of fadingdust
    fadingdust uses Amazon RDSAmazon RDS

    RDS allows us to replicate the development databases locally as well as making it available to CircleCI.

    Avatar of Chris Hartwig
    Chris Hartwig uses InfluxDBInfluxDB

    All our metrics go through InfluxDB, both applicative and system

    How much does Amazon RDS cost?
    How much does InfluxDB cost?
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