What is pgAdmin and what are its top alternatives?
Top Alternatives to pgAdmin
A cross-platform IDE that is aimed at DBAs and developers working with SQL databases. ...
OmniDB is a web tool that simplifies database management focusing on interactivity, designed to be powerful and lightweight. ...
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. ...
It is the leading graphical Open Source management, development and administration tool for PostgreSQL, running on Windows, Linux, Solaris, FreeBSD and Mac OSX ...
Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily. ...
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. ...
It is the universal database tool for developers, DBAs and analysts. It is the ultimate solution since the same tool can be used on all major operating systems accessing a wide range of databases. ...
Postico provides an easy to use interface, making Postgres more accessible for newcomers and specialists alike. Postico will look familiar to anyone who has used a Mac before. Just connect to a database and begin working with tables and views. Start with the basics and learn about advanced features of PostgreSQL as you go along. ...
pgAdmin alternatives & related posts
- Works on Linux, Windows and MacOS4
- Wide range of DBMS support2
- Code completion1
- Generate ERD1
- Quick-fixes using keyboard shortcuts1
- Code analysis1
- Database introspection on 21 different dbms1
- Export data using a variety of formats using open api1
- Import data1
- Diff viewer1
related DataGrip posts
related OmniDB posts
- Platform independent11
- Automatic driver download8
- Import-Export Data6
- Simple to use4
- Wide range of DBMS support4
- Move data between databases4
- SAP Hana DB support1
related DBeaver posts
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.
related phpPgAdmin posts
related Navicat posts
- Relational database755
- High availability508
- Enterprise class database436
- Sql + nosql302
- Great community171
- Easy to setup145
- Secure by default128
- Supports Key-Value48
- Great JSON support46
- Cross platform32
- Multiversion concurrency control21
- Open source20
- Heroku Add-on17
- Stable, Simple and Good Performance14
- Lets be serious, what other SQL DB would you go for?12
- Good documentation9
- Intelligent optimizer7
- Transactional DDL6
- One stop solution for all things sql no matter the os5
- Relational database with MVCC4
- Faster Development3
- Full-Text Search3
- Developer friendly3
- Excellent source code2
- Great DB for Transactional system or Application2
- Free version1
- Table/index bloatings9
related PostgreSQL posts
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!
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.