Alternatives to Patroni logo

Alternatives to Patroni

Citus, PostgreSQL, Slick, Spring Data, and DataGrip are the most popular alternatives and competitors to Patroni.
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What is Patroni and what are its top alternatives?

Patroni is a template for you to create your own customized, high-availability solution using Python and - for maximum accessibility - a distributed configuration store like ZooKeeper, etcd or Consul. Database engineers, DBAs, DevOps engineers, and SREs who are looking to quickly deploy HA PostgreSQL in the datacenter-or anywhere else-will hopefully find it useful.
Patroni is a tool in the Database Tools category of a tech stack.
Patroni is an open source tool with 4.4K GitHub stars and 560 GitHub forks. Here’s a link to Patroni's open source repository on GitHub

Top Alternatives to Patroni

  • Citus

    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. ...

  • PostgreSQL

    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. ...

  • 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. ...

  • DataGrip

    DataGrip

    A cross-platform IDE that is aimed at DBAs and developers working with SQL databases. ...

  • Microsoft SQL Server Management Studio

    Microsoft SQL Server Management Studio

    It is an integrated environment for managing any SQL infrastructure, from SQL Server to Azure SQL Database. It provides tools to configure, monitor, and administer instances of SQL Server and databases. Use it to deploy, monitor, and upgrade the data-tier components used by your applications, as well as build queries and scripts. ...

  • PostGIS

    PostGIS

    PostGIS is a spatial database extender for PostgreSQL object-relational database. It adds support for geographic objects allowing location queries to be run in SQL. ...

  • DBeaver

    DBeaver

    It is a free multi-platform database tool for developers, SQL programmers, database administrators and analysts. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, Teradata, MongoDB, Cassandra, Redis, etc. ...

Patroni alternatives & related posts

Citus logo

Citus

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Worry-free Postgres for SaaS
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PROS OF CITUS
  • 5
    Multi-core Parallel Processing
  • 2
    Drop-in PostgreSQL replacement
  • 2
    Distributed with Auto-Sharding
CONS OF CITUS
    Be the first to leave a con

    related Citus posts

    Dan Robinson
    Shared insights
    on
    PostgreSQLPostgreSQLCitusCitus
    at

    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

    See more
    Dan Robinson

    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

    See more
    PostgreSQL logo

    PostgreSQL

    65.4K
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    3.5K
    A powerful, open source object-relational database system
    65.4K
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    PROS OF POSTGRESQL
    • 755
      Relational database
    • 508
      High availability
    • 436
      Enterprise class database
    • 380
      Sql
    • 302
      Sql + nosql
    • 171
      Great community
    • 145
      Easy to setup
    • 129
      Heroku
    • 128
      Secure by default
    • 111
      Postgis
    • 48
      Supports Key-Value
    • 46
      Great JSON support
    • 32
      Cross platform
    • 30
      Extensible
    • 26
      Replication
    • 24
      Triggers
    • 22
      Rollback
    • 21
      Multiversion concurrency control
    • 20
      Open source
    • 17
      Heroku Add-on
    • 14
      Stable, Simple and Good Performance
    • 13
      Powerful
    • 12
      Lets be serious, what other SQL DB would you go for?
    • 9
      Good documentation
    • 7
      Intelligent optimizer
    • 7
      Scalable
    • 6
      Reliable
    • 6
      Transactional DDL
    • 6
      Modern
    • 5
      Free
    • 5
      One stop solution for all things sql no matter the os
    • 4
      Relational database with MVCC
    • 3
      Faster Development
    • 3
      Full-Text Search
    • 3
      Developer friendly
    • 2
      Excellent source code
    • 2
      Great DB for Transactional system or Application
    • 2
      search
    • 1
      Free version
    • 1
      Open-source
    • 1
      Full-text
    • 1
      Text
    CONS OF POSTGRESQL
    • 9
      Table/index bloatings

    related PostgreSQL posts

    Jeyabalaji Subramanian

    Recently we were looking at a few robust and cost-effective ways of replicating the data that resides in our production MongoDB to a PostgreSQL database for data warehousing and business intelligence.

    We set ourselves the following criteria for the optimal tool that would do this job: - The data replication must be near real-time, yet it should NOT impact the production database - The data replication must be horizontally scalable (based on the load), asynchronous & crash-resilient

    Based on the above criteria, we selected the following tools to perform the end to end data replication:

    We chose MongoDB Stitch for picking up the changes in the source database. It is the serverless platform from MongoDB. One of the services offered by MongoDB Stitch is Stitch Triggers. Using stitch triggers, you can execute a serverless function (in Node.js) in real time in response to changes in the database. When there are a lot of database changes, Stitch automatically "feeds forward" these changes through an asynchronous queue.

    We chose Amazon SQS as the pipe / message backbone for communicating the changes from MongoDB to our own replication service. Interestingly enough, MongoDB stitch offers integration with AWS services.

    In the Node.js function, we wrote minimal functionality to communicate the database changes (insert / update / delete / replace) to Amazon SQS.

    Next we wrote a minimal micro-service in Python to listen to the message events on SQS, pickup the data payload & mirror the DB changes on to the target Data warehouse. We implemented source data to target data translation by modelling target table structures through SQLAlchemy . We deployed this micro-service as AWS Lambda with Zappa. With Zappa, deploying your services as event-driven & horizontally scalable Lambda service is dumb-easy.

    In the end, we got to implement a highly scalable near realtime Change Data Replication service that "works" and deployed to production in a matter of few days!

    See more
    Tim Abbott

    We've been using PostgreSQL since the very early days of Zulip, but we actually didn't use it from the beginning. Zulip started out as a MySQL project back in 2012, because we'd heard it was a good choice for a startup with a wide community. However, we found that even though we were using the Django ORM for most of our database access, we spent a lot of time fighting with MySQL. Issues ranged from bad collation defaults, to bad query plans which required a lot of manual query tweaks.

    We ended up getting so frustrated that we tried out PostgresQL, and the results were fantastic. We didn't have to do any real customization (just some tuning settings for how big a server we had), and all of our most important queries were faster out of the box. As a result, we were able to delete a bunch of custom queries escaping the ORM that we'd written to make the MySQL query planner happy (because postgres just did the right thing automatically).

    And then after that, we've just gotten a ton of value out of postgres. We use its excellent built-in full-text search, which has helped us avoid needing to bring in a tool like Elasticsearch, and we've really enjoyed features like its partial indexes, which saved us a lot of work adding unnecessary extra tables to get good performance for things like our "unread messages" and "starred messages" indexes.

    I can't recommend it highly enough.

    See more
    Slick logo

    Slick

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    Database query and access library for Scala
    8.6K
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    PROS OF SLICK
      Be the first to leave a pro
      CONS OF SLICK
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        related Slick posts

        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
          Be the first to leave a pro
          CONS OF SPRING DATA
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            related Spring Data posts

            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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            DataGrip logo

            DataGrip

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            390
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            A database IDE for professional SQL developers
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            PROS OF DATAGRIP
            • 4
              Works on Linux, Windows and MacOS
            • 2
              Wide range of DBMS support
            • 1
              Code completion
            • 1
              Generate ERD
            • 1
              Quick-fixes using keyboard shortcuts
            • 1
              Code analysis
            • 1
              Database introspection on 21 different dbms
            • 1
              Export data using a variety of formats using open api
            • 1
              Import data
            • 1
              Diff viewer
            CONS OF DATAGRIP
              Be the first to leave a con

              related DataGrip posts

              Microsoft SQL Server Management Studio logo

              Microsoft SQL Server Management Studio

              365
              282
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              An integrated environment for managing any SQL infrastructure
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              + 1
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              PROS OF MICROSOFT SQL SERVER MANAGEMENT STUDIO
                Be the first to leave a pro
                CONS OF MICROSOFT SQL SERVER MANAGEMENT STUDIO
                  Be the first to leave a con

                  related Microsoft SQL Server Management Studio posts

                  Kelsey Doolittle

                  We have a 138 row, 1700 column database likely to grow at least a row and a column every week. We are mostly concerned with how user-friendly the graphical management tools are. I understand MySQL has MySQL WorkBench, and Microsoft SQL Server has Microsoft SQL Server Management Studio. We have about 6 months to migrate our Excel database to one of these DBMS, and continue (hopefully manually) importing excel files from then on. Any tips appreciated!

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                  PostGIS logo

                  PostGIS

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                  Open source spatial database
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                  PROS OF POSTGIS
                  • 24
                    De facto GIS in SQL
                  • 5
                    Good Documentation
                  CONS OF POSTGIS
                    Be the first to leave a con

                    related PostGIS posts

                    DBeaver logo

                    DBeaver

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                    A Universal Database Tool
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                    PROS OF DBEAVER
                    • 13
                      Free
                    • 10
                      Platform independent
                    • 8
                      Automatic driver download
                    • 6
                      Import-Export Data
                    • 4
                      Simple to use
                    • 4
                      Move data between databases
                    • 4
                      Wide range of DBMS support
                    • 1
                      SAP Hana DB support
                    • 1
                      Themes
                    CONS OF DBEAVER
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                      related DBeaver posts

                      Manikandan Shanmugam
                      Software Engineer at Blitzscaletech Software Solution · | 4 upvotes · 189.6K views
                      Shared insights
                      on
                      AzureDataStudioAzureDataStudioDBeaverDBeaver

                      Which tools are preferred if I choose to work on more data side? Which one is good if I decide to work on web development? I'm using DBeaver and am now considering a move to AzureDataStudio to break the monotony while working. I would like to hear your opinion. Which one are you using, and what are the things you are missing in dbeaver or data studio.

                      See more