Alternatives to Microsoft SQL Server logo

Alternatives to Microsoft SQL Server

Oracle, PostgreSQL, Apache Aurora, Microsoft Access, and MariaDB are the most popular alternatives and competitors to Microsoft SQL Server.
13.2K
9.7K
+ 1
535

What is Microsoft SQL Server and what are its top alternatives?

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.
Microsoft SQL Server is a tool in the Databases category of a tech stack.

Top Alternatives to Microsoft SQL Server

  • Oracle

    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. ...

  • 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. ...

  • Apache Aurora

    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. ...

  • Microsoft Access

    Microsoft Access

    It is an easy-to-use tool for creating business applications, from templates or from scratch. With its rich and intuitive design tools, it can help you create appealing and highly functional applications in a minimal amount of time. ...

  • MariaDB

    MariaDB

    Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance. ...

  • MySQL

    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. ...

  • SQLite

    SQLite

    SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file. ...

  • MongoDB

    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. ...

Microsoft SQL Server alternatives & related posts

Oracle logo

Oracle

1.6K
1.3K
107
An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism
1.6K
1.3K
+ 1
107
PROS OF ORACLE
  • 42
    Reliable
  • 31
    Enterprise
  • 15
    High Availability
  • 5
    Hard to maintain
  • 4
    Expensive
  • 4
    Maintainable
  • 3
    High complexity
  • 3
    Hard to use
CONS OF ORACLE
  • 13
    Expensive

related Oracle posts

Hi. We are planning to develop web, desktop, and mobile app for procurement, logistics, and contracts. Procure to Pay and Source to pay, spend management, supplier management, catalog management. ( similar to SAP Ariba, gap.com, coupa.com, ivalua.com vroozi.com, procurify.com

We got stuck when deciding which technology stack is good for the future. We look forward to your kind guidance that will help us.

We want to integrate with multiple databases with seamless bidirectional integration. What APIs and middleware available are best to achieve this? SAP HANA, Oracle, MySQL, MongoDB...

ASP.NET / Node.js / Laravel. ......?

Please guide us

See more
PostgreSQL logo

PostgreSQL

65.6K
52.6K
3.5K
A powerful, open source object-relational database system
65.6K
52.6K
+ 1
3.5K
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
Apache Aurora logo

Apache Aurora

63
82
0
An Apcahe Mesos framework for scheduling jobs, originally developed by Twitter
63
82
+ 1
0
PROS OF APACHE AURORA
    Be the first to leave a pro
    CONS OF APACHE AURORA
      Be the first to leave a con

      related Apache Aurora posts

      Docker containers on Mesos run their microservices with consistent configurations at scale, along with Aurora for long-running services and cron jobs.

      See more
      Microsoft Access logo

      Microsoft Access

      55
      52
      0
      A database management system
      55
      52
      + 1
      0
      PROS OF MICROSOFT ACCESS
        Be the first to leave a pro
        CONS OF MICROSOFT ACCESS
          Be the first to leave a con

          related Microsoft Access posts

          MariaDB logo

          MariaDB

          11.3K
          8.5K
          467
          An enhanced, drop-in replacement for MySQL
          11.3K
          8.5K
          + 1
          467
          PROS OF MARIADB
          • 149
            Drop-in mysql replacement
          • 100
            Great performance
          • 74
            Open source
          • 54
            Free
          • 44
            Easy setup
          • 15
            Easy and fast
          • 14
            Lead developer is "monty" widenius the founder of mysql
          • 6
            Also an aws rds service
          • 4
            Learning curve easy
          • 4
            Consistent and robust
          • 2
            Native JSON Support / Dynamic Columns
          • 1
            Real Multi Threaded queries on a table/db
          CONS OF MARIADB
            Be the first to leave a con

            related MariaDB posts

            Joshua Dean Küpper
            CEO at Scrayos UG (haftungsbeschränkt) · | 11 upvotes · 280.6K views

            We primarily use MariaDB but use PostgreSQL as a part of GitLab , Sentry and Nextcloud , which (initially) forced us to use it anyways. While this isn't much of a decision – because we didn't have one (ha ha) – we learned to love the perks and advantages of PostgreSQL anyways. PostgreSQL's extension system makes it even more flexible than a lot of the other SQL-based DBs (that only offer stored procedures) and the additional JOIN options, the enhanced role management and the different authentication options came in really handy, when doing manual maintenance on the databases.

            See more

            I'm researching what Technology Stack I should use to build my product (something like food delivery App) for Web, iOS, and Android Apps. Please advise which technologies you would recommend from a Scalability, Reliability, Cost, and Efficiency standpoint for a start-up. Here are the technologies I came up with, feel free to suggest any new technology even it's not in the list below.

            For Mobile Apps -

            1. native languages like Swift for IOS and Java/Kotlin for Android
            2. or cross-platform languages like React Native for both IOS and Android Apps

            For UI -

            1. React

            For Back-End or APIs -

            1. Node.js
            2. PHP

            For Database -

            1. PostgreSQL
            2. MySQL
            3. Cloud Firestore
            4. MariaDB

            Thanks!

            See more
            MySQL logo

            MySQL

            85.8K
            69.5K
            3.7K
            The world's most popular open source database
            85.8K
            69.5K
            + 1
            3.7K
            PROS OF MYSQL
            • 793
              Sql
            • 672
              Free
            • 556
              Easy
            • 527
              Widely used
            • 485
              Open source
            • 180
              High availability
            • 160
              Cross-platform support
            • 104
              Great community
            • 78
              Secure
            • 75
              Full-text indexing and searching
            • 25
              Fast, open, available
            • 14
              SSL support
            • 13
              Reliable
            • 13
              Robust
            • 8
              Enterprise Version
            • 7
              Easy to set up on all platforms
            • 2
              NoSQL access to JSON data type
            • 1
              Relational database
            • 1
              Easy, light, scalable
            • 1
              Sequel Pro (best SQL GUI)
            • 1
              Replica Support
            CONS OF MYSQL
            • 14
              Owned by a company with their own agenda
            • 1
              Can't roll back schema changes

            related MySQL posts

            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
            Conor Myhrvold
            Tech Brand Mgr, Office of CTO at Uber · | 21 upvotes · 1.1M views

            Our most popular (& controversial!) article to date on the Uber Engineering blog in 3+ yrs. Why we moved from PostgreSQL to MySQL. In essence, it was due to a variety of limitations of Postgres at the time. Fun fact -- earlier in Uber's history we'd actually moved from MySQL to Postgres before switching back for good, & though we published the article in Summer 2016 we haven't looked back since:

            The early architecture of Uber consisted of a monolithic backend application written in Python that used Postgres for data persistence. Since that time, the architecture of Uber has changed significantly, to a model of microservices and new data platforms. Specifically, in many of the cases where we previously used Postgres, we now use Schemaless, a novel database sharding layer built on top of MySQL (https://eng.uber.com/schemaless-part-one/). In this article, we’ll explore some of the drawbacks we found with Postgres and explain the decision to build Schemaless and other backend services on top of MySQL:

            https://eng.uber.com/mysql-migration/

            See more
            SQLite logo

            SQLite

            12.3K
            9.7K
            528
            A software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine
            12.3K
            9.7K
            + 1
            528
            PROS OF SQLITE
            • 160
              Lightweight
            • 134
              Portable
            • 121
              Simple
            • 80
              Sql
            • 28
              Preinstalled on iOS and Android
            • 2
              Tcl integration
            • 1
              Free
            • 1
              Telefon
            • 1
              Portable A database on my USB 'love it'
            CONS OF SQLITE
            • 2
              Not for multi-process of multithreaded apps
            • 1
              Needs different binaries for each platform

            related SQLite posts

            Dimelo Waterson
            Shared insights
            on
            PostgreSQLPostgreSQLMySQLMySQLSQLiteSQLite

            I need to add a DBMS to my stack, but I don't know which. I'm tempted to learn SQLite since it would be useful to me with its focus on local access without concurrency. However, doing so feels like I would be defeating the purpose of trying to expand my skill set since it seems like most enterprise applications have the opposite requirements.

            To be able to apply what I learn to more projects, what should I try to learn? MySQL? PostgreSQL? Something else? Is there a comfortable middle ground between high applicability and ease of use?

            See more
            Christian Stefanescu
            Head of IT at lawpilots · | 3 upvotes · 11.4K views
            Shared insights
            on
            DjangoDjangoSQLiteSQLitePostgreSQLPostgreSQL

            While I love and use PostgreSQL , I would definitely recommend having a look at SQLite as well. It can be a solid database for lots of applications and it brings some advantages in terms of handling: you don't need a server running, which makes things like testing, deploying or backing up databases much easier. Through the ORM in Django you are one abstraction level away from your database anyway and switching later on is definitely an option, but I believe SQLite is very good for pretty much all the small applications you can think of.

            See more
            MongoDB logo

            MongoDB

            64.9K
            54.1K
            4.1K
            The database for giant ideas
            64.9K
            54.1K
            + 1
            4.1K
            PROS OF MONGODB
            • 824
              Document-oriented storage
            • 591
              No sql
            • 546
              Ease of use
            • 465
              Fast
            • 406
              High performance
            • 256
              Free
            • 215
              Open source
            • 179
              Flexible
            • 142
              Replication & high availability
            • 109
              Easy to maintain
            • 41
              Querying
            • 37
              Easy scalability
            • 36
              Auto-sharding
            • 35
              High availability
            • 31
              Map/reduce
            • 26
              Document database
            • 24
              Easy setup
            • 24
              Full index support
            • 15
              Reliable
            • 14
              Fast in-place updates
            • 13
              Agile programming, flexible, fast
            • 11
              No database migrations
            • 7
              Easy integration with Node.Js
            • 7
              Enterprise
            • 5
              Enterprise Support
            • 4
              Great NoSQL DB
            • 3
              Aggregation Framework
            • 3
              Support for many languages through different drivers
            • 3
              Drivers support is good
            • 2
              Schemaless
            • 2
              Easy to Scale
            • 2
              Fast
            • 2
              Awesome
            • 2
              Managed service
            • 1
              Consistent
            CONS OF MONGODB
            • 5
              Very slowly for connected models that require joins
            • 3
              Not acid compliant
            • 1
              Proprietary query language

            related MongoDB 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
            Robert Zuber

            We use MongoDB as our primary #datastore. Mongo's approach to replica sets enables some fantastic patterns for operations like maintenance, backups, and #ETL.

            As we pull #microservices from our #monolith, we are taking the opportunity to build them with their own datastores using PostgreSQL. We also use Redis to cache data we’d never store permanently, and to rate-limit our requests to partners’ APIs (like GitHub).

            When we’re dealing with large blobs of immutable data (logs, artifacts, and test results), we store them in Amazon S3. We handle any side-effects of S3’s eventual consistency model within our own code. This ensures that we deal with user requests correctly while writes are in process.

            See more