Alternatives to Microsoft Access logo

Alternatives to Microsoft Access

Oracle, MySQL, Power BI, FileMaker, and Google Sheets are the most popular alternatives and competitors to Microsoft Access.
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What is Microsoft Access and what are its top alternatives?

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.
Microsoft Access is a tool in the Databases category of a tech stack.

Top Alternatives to Microsoft Access

  • 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. ...

  • 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. ...

  • Power BI

    Power BI

    It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. ...

  • FileMaker

    FileMaker

    It is a Platform to create innovative custom apps for your workplace.

  • Google Sheets

    Google Sheets

    Access, create, and edit your spreadsheets wherever you go—from your phone, tablet, or computer. ...

  • Airtable

    Airtable

    Working with Airtable is as fast and easy as editing a spreadsheet. But only Airtable is backed by the power of a full database, giving you rich features far beyond what a spreadsheet can offer. ...

  • 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. ...

  • 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 Access alternatives & related posts

Oracle logo

Oracle

1.5K
1.2K
106
An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism
1.5K
1.2K
+ 1
106
PROS OF ORACLE
  • 42
    Reliable
  • 30
    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
MySQL logo

MySQL

77.4K
61.5K
3.7K
The world's most popular open source database
77.4K
61.5K
+ 1
3.7K
PROS OF MYSQL
  • 790
    Sql
  • 673
    Free
  • 557
    Easy
  • 525
    Widely used
  • 485
    Open source
  • 180
    High availability
  • 158
    Cross-platform support
  • 103
    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
    Replica Support
  • 1
    Easy, light, scalable
  • 1
    Relational database
  • 1
    Sequel Pro (best SQL GUI)
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 · 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
Power BI logo

Power BI

470
453
5
Empower team members to discover insights hidden in your data
470
453
+ 1
5
PROS OF POWER BI
  • 5
    Cross-filtering
CONS OF POWER BI
    Be the first to leave a con

    related Power BI posts

    Looking for the best analytics software for a medium-large-sized firm. We currently use a Microsoft SQL Server database that is analyzed in Tableau desktop/published to Tableau online for users to access dashboards. Is it worth the cost savings/time to switch over to using SSRS or Power BI? Does anyone have experience migrating from Tableau to SSRS /or Power BI? Our other option is to consider using Tableau on-premises instead of online. Using custom SQL with over 3 million rows really decreases performances and results in processing times that greatly exceed our typical experience. Thanks.

    See more
    FileMaker logo

    FileMaker

    22
    26
    6
    Platform to easily create custom apps that manage user contact
    22
    26
    + 1
    6
    PROS OF FILEMAKER
    • 1
      API
    • 1
      REST API
    • 1
      Permissions
    • 1
      All included
    • 1
      Easy to learn
    • 1
      Rapid development
    CONS OF FILEMAKER
    • 1
      Expensive

    related FileMaker posts

    Google Sheets logo

    Google Sheets

    816
    575
    10
    Create and edit spreadsheets online, for free
    816
    575
    + 1
    10
    PROS OF GOOGLE SHEETS
    • 8
      Simultaneous shared editing
    • 2
      Online alternative to MS Excel
    CONS OF GOOGLE SHEETS
      Be the first to leave a con

      related Google Sheets posts

      Jason Barry
      Cofounder at FeaturePeek · | 10 upvotes · 152.4K views

      If you're a developer using Google Docs or Google Sheets... just stop. There are much better alternatives these days that provide a better user and developer experience.

      At FeaturePeek, we use slite for our internal documents and knowledge tracking. Slite's look and feel is similar to Slack's, so if you use Slack, you'll feel right at home. Slite is great for keeping tabs on meeting notes, internal documentation, drafting marketing content, writing pitches... any long-form text writing that we do as a company happens in Slite. I'm able to be up-to-date with everyone on my team by viewing our team activity. I feel more organized using Slite as opposed to GDocs or GDrive.

      Airtable is also absolutely killer – you'll never want to use Google Sheets again. Have you noticed that with most spreadsheet apps, if you have a tall or wide cell, your screen jumps all over the place when you scroll? With Airtable, you can scroll by screen pixels instead of by spreadsheet cells – this makes a huge difference! It's one of those things that you don't really notice at first, but once you do, you can't go back. This is just one example of the UX improvements that Airtable has to the previous generation of spreadsheet apps – there are plenty more.

      Also, their API is a breeze to use. If you're logged in, the docs fill in values from your tables and account, so it feels personalized to you.

      See more
      Airtable logo

      Airtable

      697
      615
      36
      Real-time spreadsheet-database hybrid
      697
      615
      + 1
      36
      PROS OF AIRTABLE
      • 18
        Powerful and easy to use
      • 8
        Robust and dynamic
      • 4
        Quick UI Layer
      • 3
        Robust API documentation
      • 3
        Practical built in views
      • 0
        Great flexibility
      CONS OF AIRTABLE
        Be the first to leave a con

        related Airtable posts

        Jason Barry
        Cofounder at FeaturePeek · | 10 upvotes · 152.4K views

        If you're a developer using Google Docs or Google Sheets... just stop. There are much better alternatives these days that provide a better user and developer experience.

        At FeaturePeek, we use slite for our internal documents and knowledge tracking. Slite's look and feel is similar to Slack's, so if you use Slack, you'll feel right at home. Slite is great for keeping tabs on meeting notes, internal documentation, drafting marketing content, writing pitches... any long-form text writing that we do as a company happens in Slite. I'm able to be up-to-date with everyone on my team by viewing our team activity. I feel more organized using Slite as opposed to GDocs or GDrive.

        Airtable is also absolutely killer – you'll never want to use Google Sheets again. Have you noticed that with most spreadsheet apps, if you have a tall or wide cell, your screen jumps all over the place when you scroll? With Airtable, you can scroll by screen pixels instead of by spreadsheet cells – this makes a huge difference! It's one of those things that you don't really notice at first, but once you do, you can't go back. This is just one example of the UX improvements that Airtable has to the previous generation of spreadsheet apps – there are plenty more.

        Also, their API is a breeze to use. If you're logged in, the docs fill in values from your tables and account, so it feels personalized to you.

        See more
        PostgreSQL logo

        PostgreSQL

        58.4K
        46.2K
        3.5K
        A powerful, open source object-relational database system
        58.4K
        46.2K
        + 1
        3.5K
        PROS OF POSTGRESQL
        • 754
          Relational database
        • 506
          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
        • 29
          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
          Transactional DDL
        • 6
          Modern
        • 6
          Reliable
        • 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
          search
        • 2
          Great DB for Transactional system or Application
        • 1
          Full-text
        • 1
          Free version
        • 1
          Text
        • 1
          Open-source
        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
        MongoDB logo

        MongoDB

        58.1K
        47.7K
        4.1K
        The database for giant ideas
        58.1K
        47.7K
        + 1
        4.1K
        PROS OF MONGODB
        • 822
          Document-oriented storage
        • 589
          No sql
        • 545
          Ease of use
        • 464
          Fast
        • 405
          High performance
        • 254
          Free
        • 214
          Open source
        • 178
          Flexible
        • 141
          Replication & high availability
        • 108
          Easy to maintain
        • 40
          Querying
        • 36
          Easy scalability
        • 35
          Auto-sharding
        • 34
          High availability
        • 30
          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
          Enterprise
        • 7
          Easy integration with Node.Js
        • 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
          Fast
        • 2
          Awesome
        • 2
          Managed service
        • 2
          Easy to Scale
        • 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