Alternatives to Tardigrade logo

Alternatives to Tardigrade

Anaconda, Amazon S3, Google Cloud Storage, Amazon EBS, and Azure Storage are the most popular alternatives and competitors to Tardigrade.
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What is Tardigrade and what are its top alternatives?

It is the enterprise, production-ready version of storjproject's decentralized cloud storage network. Ridiculously resilient, highly distributed. It is the perfect alternative to Amazon S3 -- in fact, it's S3 compatible so you can build your product using it as your backend storage layer without any issues.
Tardigrade is a tool in the Cloud Storage category of a tech stack.

Top Alternatives to Tardigrade

  • Anaconda

    Anaconda

    A free and open-source distribution of the Python and R programming languages for scientific computing, that aims to simplify package management and deployment. Package versions are managed by the package management system conda. ...

  • Amazon S3

    Amazon S3

    Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web ...

  • Google Cloud Storage

    Google Cloud Storage

    Google Cloud Storage allows world-wide storing and retrieval of any amount of data and at any time. It provides a simple programming interface which enables developers to take advantage of Google's own reliable and fast networking infrastructure to perform data operations in a secure and cost effective manner. If expansion needs arise, developers can benefit from the scalability provided by Google's infrastructure. ...

  • Amazon EBS

    Amazon EBS

    Amazon EBS volumes are network-attached, and persist independently from the life of an instance. Amazon EBS provides highly available, highly reliable, predictable storage volumes that can be attached to a running Amazon EC2 instance and exposed as a device within the instance. Amazon EBS is particularly suited for applications that require a database, file system, or access to raw block level storage. ...

  • Azure Storage

    Azure Storage

    Azure Storage provides the flexibility to store and retrieve large amounts of unstructured data, such as documents and media files with Azure Blobs; structured nosql based data with Azure Tables; reliable messages with Azure Queues, and use SMB based Azure Files for migrating on-premises applications to the cloud. ...

  • Minio

    Minio

    Minio is an object storage server compatible with Amazon S3 and licensed under Apache 2.0 License ...

  • iCloud

    iCloud

    Sign in to iCloud to access your photos, videos, documents, notes, contacts, and more. Use your Apple ID or create a new account to start using Apple services. ...

  • Rackspace Cloud Files

    Rackspace Cloud Files

    Cloud Files, powered by OpenStack®, provides an easy to use online storage for files and media which can be delivered globally at blazing speeds over Akamai's content delivery network (CDN). ...

Tardigrade alternatives & related posts

Anaconda logo

Anaconda

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The Enterprise Data Science Platform for Data Scientists, IT Professionals and Business Leaders
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PROS OF ANACONDA
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      Shared insights
      on
      JavaJavaAnacondaAnacondaPythonPython

      I am going to learn machine learning and self host an online IDE, the tool that i may use is Python, Anaconda, various python library and etc. which tools should i go for? this may include Java development, web development. Now i have 1 more candidate which are visual studio code online (code server). i will host on google cloud

      See more
      Guillaume Simler

      Jupyter Anaconda Pandas IPython

      A great way to prototype your data analytic modules. The use of the package is simple and user-friendly and the migration from ipython to python is fairly simple: a lot of cleaning, but no more.

      The negative aspect comes when you want to streamline your productive system or does CI with your anaconda environment: - most tools don't accept conda environments (as smoothly as pip requirements) - the conda environments (even with miniconda) have quite an overhead

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      Amazon S3 logo

      Amazon S3

      41.7K
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      Store and retrieve any amount of data, at any time, from anywhere on the web
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      PROS OF AMAZON S3
      • 591
        Reliable
      • 492
        Scalable
      • 456
        Cheap
      • 328
        Simple & easy
      • 83
        Many sdks
      • 29
        Logical
      • 12
        Easy Setup
      • 11
        1000+ POPs
      • 10
        REST API
      • 5
        Secure
      • 3
        Easy
      • 2
        Web UI for uploading files
      • 2
        Plug and play
      • 1
        GDPR ready
      • 1
        Flexible
      • 1
        Faster on response
      • 1
        Plug-gable
      • 1
        Easy to use
      • 1
        Easy integration with CloudFront
      CONS OF AMAZON S3
      • 7
        Permissions take some time to get right
      • 6
        Takes time/work to organize buckets & folders properly
      • 5
        Requires a credit card
      • 3
        Complex to set up

      related Amazon S3 posts

      Ashish Singh
      Tech Lead, Big Data Platform at Pinterest · | 36 upvotes · 922.4K views

      To provide employees with the critical need of interactive querying, we’ve worked with Presto, an open-source distributed SQL query engine, over the years. Operating Presto at Pinterest’s scale has involved resolving quite a few challenges like, supporting deeply nested and huge thrift schemas, slow/ bad worker detection and remediation, auto-scaling cluster, graceful cluster shutdown and impersonation support for ldap authenticator.

      Our infrastructure is built on top of Amazon EC2 and we leverage Amazon S3 for storing our data. This separates compute and storage layers, and allows multiple compute clusters to share the S3 data.

      We have hundreds of petabytes of data and tens of thousands of Apache Hive tables. Our Presto clusters are comprised of a fleet of 450 r4.8xl EC2 instances. Presto clusters together have over 100 TBs of memory and 14K vcpu cores. Within Pinterest, we have close to more than 1,000 monthly active users (out of total 1,600+ Pinterest employees) using Presto, who run about 400K queries on these clusters per month.

      Each query submitted to Presto cluster is logged to a Kafka topic via Singer. Singer is a logging agent built at Pinterest and we talked about it in a previous post. Each query is logged when it is submitted and when it finishes. When a Presto cluster crashes, we will have query submitted events without corresponding query finished events. These events enable us to capture the effect of cluster crashes over time.

      Each Presto cluster at Pinterest has workers on a mix of dedicated AWS EC2 instances and Kubernetes pods. Kubernetes platform provides us with the capability to add and remove workers from a Presto cluster very quickly. The best-case latency on bringing up a new worker on Kubernetes is less than a minute. However, when the Kubernetes cluster itself is out of resources and needs to scale up, it can take up to ten minutes. Some other advantages of deploying on Kubernetes platform is that our Presto deployment becomes agnostic of cloud vendor, instance types, OS, etc.

      #BigData #AWS #DataScience #DataEngineering

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      Simon Reymann
      Senior Fullstack Developer at QUANTUSflow Software GmbH · | 28 upvotes · 3.5M views

      Our whole DevOps stack consists of the following tools:

      • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
      • Respectively Git as revision control system
      • SourceTree as Git GUI
      • Visual Studio Code as IDE
      • CircleCI for continuous integration (automatize development process)
      • Prettier / TSLint / ESLint as code linter
      • SonarQube as quality gate
      • Docker as container management (incl. Docker Compose for multi-container application management)
      • VirtualBox for operating system simulation tests
      • Kubernetes as cluster management for docker containers
      • Heroku for deploying in test environments
      • nginx as web server (preferably used as facade server in production environment)
      • SSLMate (using OpenSSL) for certificate management
      • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
      • PostgreSQL as preferred database system
      • Redis as preferred in-memory database/store (great for caching)

      The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

      • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
      • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
      • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
      • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
      • Scalability: All-in-one framework for distributed systems.
      • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
      See more
      Google Cloud Storage logo

      Google Cloud Storage

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      Durable and highly available object storage service
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      PROS OF GOOGLE CLOUD STORAGE
      • 28
        Scalable
      • 18
        Cheap
      • 14
        Reliable
      • 9
        Easy
      • 3
        Chealp
      • 1
        More praticlal and easy
      CONS OF GOOGLE CLOUD STORAGE
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        related Google Cloud Storage posts

        Aliadoc Team

        In #Aliadoc, we're exploring the crowdfunding option to get traction before launch. We are building a SaaS platform for website design customization.

        For the Admin UI and website editor we use React and we're currently transitioning from a Create React App setup to a custom one because our needs have become more specific. We use CloudFlare as much as possible, it's a great service.

        For routing dynamic resources and proxy tasks to feed websites to the editor we leverage CloudFlare Workers for improved responsiveness. We use Firebase for our hosting needs and user authentication while also using several Cloud Functions for Firebase to interact with other services along with Google App Engine and Google Cloud Storage, but also the Real Time Database is on the radar for collaborative website editing.

        We generally hate configuration but honestly because of the stage of our project we lack resources for doing heavy sysops work. So we are basically just relying on Serverless technologies as much as we can to do all server side processing.

        Visual Studio Code definitively makes programming a much easier and enjoyable task, we just love it. We combine it with Bitbucket for our source code control needs.

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        Amazon EBS logo

        Amazon EBS

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        Block level storage volumes for use with Amazon EC2 instances.
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        PROS OF AMAZON EBS
        • 36
          Point-in-time snapshots
        • 27
          Data reliability
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          Configurable i/o performance
        CONS OF AMAZON EBS
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          related Amazon EBS posts

          We are looking for a centralised monitoring solution for our application deployed on Amazon EKS. We would like to monitor using metrics from Kubernetes, AWS services (NeptuneDB, AWS Elastic Load Balancing (ELB), Amazon EBS, Amazon S3, etc) and application microservice's custom metrics.

          We are expected to use around 80 microservices (not replicas). I think a total of 200-250 microservices will be there in the system with 10-12 slave nodes.

          We tried Prometheus but it looks like maintenance is a big issue. We need to manage scaling, maintaining the storage, and dealing with multiple exporters and Grafana. I felt this itself needs few dedicated resources (at least 2-3 people) to manage. Not sure if I am thinking in the correct direction. Please confirm.

          You mentioned Datadog and Sysdig charges per host. Does it charge per slave node?

          See more
          Azure Storage logo

          Azure Storage

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          Reliable, economical cloud storage for data big and small
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          PROS OF AZURE STORAGE
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            All-in-one storage solution
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            Pay only for data used regardless of disk size
          • 9
            Shared drive mapping
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            Cost-effective
          • 2
            Cheapest hot and cloud storage
          CONS OF AZURE STORAGE
          • 2
            Direct support is not provided by Azure storage

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          Minio logo

          Minio

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          AWS S3 open source alternative written in Go
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          PROS OF MINIO
          • 8
            Store and Serve Resumes & Job Description PDF, Backups
          • 5
            S3 Compatible
          • 4
            Simple
          • 4
            Open Source
          • 3
            Encryption and Tamper-Proof
          • 2
            Highly Available
          • 2
            Pluggable Storage Backend
          • 2
            Lambda Compute
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            Private Cloud Storage
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            Scalable
          • 2
            Data Protection
          • 1
            Performance
          CONS OF MINIO
          • 2
            Deletion of huge buckets is not possible

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          iCloud logo

          iCloud

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          A cloud storage and cloud computing service
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          PROS OF ICLOUD
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              related iCloud posts

              I'm looking for a tool or set of tools to enable searching across all of our platforms including Confluence and Jira, Zoho CRM, Gmail, Gdrive for business, Dropbox and iCloud.

              Any ideas. Something like X1? IBM Watson Discovery?

              (And local Disk of course)

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              Rackspace Cloud Files logo

              Rackspace Cloud Files

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              Store it on Cloud Files, serve it fast on Akamai's CDN
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              PROS OF RACKSPACE CLOUD FILES
              • 5
                Akamai CDN
              • 5
                Inexpensive and pay-as-you-go
              • 4
                Simple file upload
              • 3
                Simple scaling
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                Any media type, any size
              • 2
                Huge time-saver
              • 1
                Easy deployment
              • 1
                Low learning curve
              • 1
                Beginner friendly
              • 1
                Great costumer support
              CONS OF RACKSPACE CLOUD FILES
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                related Rackspace Cloud Files posts