Alternatives to Studio 3T logo

Alternatives to Studio 3T

Robo 3T, Compass, NoSQLBooster, Navicat, and MongoDB Compass are the most popular alternatives and competitors to Studio 3T.
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What is Studio 3T and what are its top alternatives?

It's the only MongoDB tool that provides three ways to explore data alongside powerful features like query autocompletion, polyglot code generation, a stage-by-stage aggregation query builder, import and export, SQL query support and more.
Studio 3T is a tool in the Virtual Machine Platforms & Containers category of a tech stack.
Studio 3T is an open source tool with GitHub stars and GitHub forks. Here’s a link to Studio 3T's open source repository on GitHub

Top Alternatives to Studio 3T

  • Robo 3T

    Robo 3T

    It is a visual tool helping you manage Database MongoDB. It is a part of free open source software supporting all of three operating systems: Windows, Linux, Mac OS. ...

  • Compass

    Compass

    The compass core framework is a design-agnostic framework that provides common code that would otherwise be duplicated across other frameworks and extensions. ...

  • NoSQLBooster

    NoSQLBooster

    It is a shell-centric cross-platform GUI tool for MongoDB v2.6-4.0 which provides comprehensive server monitoring tools, fluent query builder, SQL query, ES2017 syntax support and true intellisense experience. ...

  • Navicat

    Navicat

    Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily. ...

  • MongoDB Compass

    MongoDB Compass

    Visually explore your data. Run ad hoc queries in seconds. Interact with your data with full CRUD functionality. View and optimize your query performance. ...

  • Docker

    Docker

    The Docker Platform is the industry-leading container platform for continuous, high-velocity innovation, enabling organizations to seamlessly build and share any application — from legacy to what comes next — and securely run them anywhere ...

  • Slick

    Slick

    It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred. ...

  • Spring Data

    Spring Data

    It makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. This is an umbrella project which contains many subprojects that are specific to a given database. ...

Studio 3T alternatives & related posts

Robo 3T logo

Robo 3T

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A lightweight GUI for MongoDB
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PROS OF ROBO 3T
    No pros available
    CONS OF ROBO 3T
      No cons available

      related Robo 3T posts

      Compass logo

      Compass

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      A Stylesheet Authoring Environment that makes your website design simpler to implement and easier to maintain
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      CONS OF COMPASS
        No cons available

        related Compass posts

        NoSQLBooster logo

        NoSQLBooster

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        MongoDB Admin GUI tool
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        PROS OF NOSQLBOOSTER
          No pros available
          CONS OF NOSQLBOOSTER
            No cons available

            related NoSQLBooster posts

            Navicat logo

            Navicat

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            A comprehensive DB tool for MySQL, MariaDB, SQL Server, SQLite, Oracle and PostgreSQL development and management.
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            PROS OF NAVICAT
            CONS OF NAVICAT
              No cons available

              related Navicat posts

              MongoDB Compass logo

              MongoDB Compass

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              A GUI for MongoDB
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              PROS OF MONGODB COMPASS
                No pros available
                CONS OF MONGODB COMPASS
                  No cons available

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                  related Docker posts

                  Simon Reymann
                  Senior Fullstack Developer at QUANTUSflow Software GmbH · | 27 upvotes · 1.8M 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.
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                  Tymoteusz Paul
                  Devops guy at X20X Development LTD · | 21 upvotes · 3.8M views

                  Often enough I have to explain my way of going about setting up a CI/CD pipeline with multiple deployment platforms. Since I am a bit tired of yapping the same every single time, I've decided to write it up and share with the world this way, and send people to read it instead ;). I will explain it on "live-example" of how the Rome got built, basing that current methodology exists only of readme.md and wishes of good luck (as it usually is ;)).

                  It always starts with an app, whatever it may be and reading the readmes available while Vagrant and VirtualBox is installing and updating. Following that is the first hurdle to go over - convert all the instruction/scripts into Ansible playbook(s), and only stopping when doing a clear vagrant up or vagrant reload we will have a fully working environment. As our Vagrant environment is now functional, it's time to break it! This is the moment to look for how things can be done better (too rigid/too lose versioning? Sloppy environment setup?) and replace them with the right way to do stuff, one that won't bite us in the backside. This is the point, and the best opportunity, to upcycle the existing way of doing dev environment to produce a proper, production-grade product.

                  I should probably digress here for a moment and explain why. I firmly believe that the way you deploy production is the same way you should deploy develop, shy of few debugging-friendly setting. This way you avoid the discrepancy between how production work vs how development works, which almost always causes major pains in the back of the neck, and with use of proper tools should mean no more work for the developers. That's why we start with Vagrant as developer boxes should be as easy as vagrant up, but the meat of our product lies in Ansible which will do meat of the work and can be applied to almost anything: AWS, bare metal, docker, LXC, in open net, behind vpn - you name it.

                  We must also give proper consideration to monitoring and logging hoovering at this point. My generic answer here is to grab Elasticsearch, Kibana, and Logstash. While for different use cases there may be better solutions, this one is well battle-tested, performs reasonably and is very easy to scale both vertically (within some limits) and horizontally. Logstash rules are easy to write and are well supported in maintenance through Ansible, which as I've mentioned earlier, are at the very core of things, and creating triggers/reports and alerts based on Elastic and Kibana is generally a breeze, including some quite complex aggregations.

                  If we are happy with the state of the Ansible it's time to move on and put all those roles and playbooks to work. Namely, we need something to manage our CI/CD pipelines. For me, the choice is obvious: TeamCity. It's modern, robust and unlike most of the light-weight alternatives, it's transparent. What I mean by that is that it doesn't tell you how to do things, doesn't limit your ways to deploy, or test, or package for that matter. Instead, it provides a developer-friendly and rich playground for your pipelines. You can do most the same with Jenkins, but it has a quite dated look and feel to it, while also missing some key functionality that must be brought in via plugins (like quality REST API which comes built-in with TeamCity). It also comes with all the common-handy plugins like Slack or Apache Maven integration.

                  The exact flow between CI and CD varies too greatly from one application to another to describe, so I will outline a few rules that guide me in it: 1. Make build steps as small as possible. This way when something breaks, we know exactly where, without needing to dig and root around. 2. All security credentials besides development environment must be sources from individual Vault instances. Keys to those containers should exist only on the CI/CD box and accessible by a few people (the less the better). This is pretty self-explanatory, as anything besides dev may contain sensitive data and, at times, be public-facing. Because of that appropriate security must be present. TeamCity shines in this department with excellent secrets-management. 3. Every part of the build chain shall consume and produce artifacts. If it creates nothing, it likely shouldn't be its own build. This way if any issue shows up with any environment or version, all developer has to do it is grab appropriate artifacts to reproduce the issue locally. 4. Deployment builds should be directly tied to specific Git branches/tags. This enables much easier tracking of what caused an issue, including automated identifying and tagging the author (nothing like automated regression testing!).

                  Speaking of deployments, I generally try to keep it simple but also with a close eye on the wallet. Because of that, I am more than happy with AWS or another cloud provider, but also constantly peeking at the loads and do we get the value of what we are paying for. Often enough the pattern of use is not constantly erratic, but rather has a firm baseline which could be migrated away from the cloud and into bare metal boxes. That is another part where this approach strongly triumphs over the common Docker and CircleCI setup, where you are very much tied in to use cloud providers and getting out is expensive. Here to embrace bare-metal hosting all you need is a help of some container-based self-hosting software, my personal preference is with Proxmox and LXC. Following that all you must write are ansible scripts to manage hardware of Proxmox, similar way as you do for Amazon EC2 (ansible supports both greatly) and you are good to go. One does not exclude another, quite the opposite, as they can live in great synergy and cut your costs dramatically (the heavier your base load, the bigger the savings) while providing production-grade resiliency.

                  See more
                  Slick logo

                  Slick

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                  Database query and access library for Scala
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                  PROS OF SLICK
                    No pros available
                    CONS OF SLICK
                      No cons available

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                      Spring Data logo

                      Spring Data

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                      Provides a consistent approach to data access – relational, non-relational, map-reduce, and beyond
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                      PROS OF SPRING DATA
                        No pros available
                        CONS OF SPRING DATA
                          No cons available

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                          Остап Комплікевич

                          I need some advice to choose an engine for generation web pages from the Spring Boot app. Which technology is the best solution today? 1) JSP + JSTL 2) Apache FreeMarker 3) Thymeleaf Or you can suggest even other perspective tools. I am using Spring Boot, Spring Web, Spring Data, Spring Security, PostgreSQL, Apache Tomcat in my project. I have already tried to generate pages using jsp, jstl, and it went well. However, I had huge problems via carrying already created static pages, to jsp format, because of syntax. Thanks.

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