PostgreSQL is a Well Poised for the Future, Venerable, More Than a Database Solution for Many
October 12, 2019

PostgreSQL is a Well Poised for the Future, Venerable, More Than a Database Solution for Many

Arthur Zubarev | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with PostgreSQL

PostgreSQL is used across the entire organization and in more than one instance. PostgreSQL was already a part of a wide scale Ruby On Rails implementation and thus was a natural fit for the use in data analytics in form of data marts, data inter-exchange, reporting, and ad-hoc data storage and retrieval.
PostgreSQL fulfills a role of a dedicated and/or per-application or solution data storage engine. Its versatility and flexibility combined with exceptional user community support make a stand-out product. Integration or migration with AWS Redshift is easy and seamless. PostgreSQL has a near-complete ANSI SQL language implementation which makes it very handy for data extraction and analytics.
  • Flexibility and Unicode compliance combined with nearly full SQL features support makes PostgreSQL an ideal tool to conducting complex data analyses
  • Ease of administering PostgreSQL, SSL, SSO support make it possible to operate a very private and secure data repository
  • Programmability of PostgreSQL is superb. Multiple standard programming languages are supported, PL/SQL flavour of programming is possible
  • PostgreSQL runs on any platform
  • Replication, high availability are some of the enterprise features that anyone can implement on its own
  • Free, relatively mature for everyday use client tools
  • Most languages have native drivers
  • Superb support for JSON makes it not stop by thinking of NoSQL
  • Not exactly parallel, means a single query often is run in a sequential manner, no threads. The optimizer is hard to understand and deliver quicker queries faster is not often possible (MVCC model)
  • Index operations are slow
  • Can chew up on the CPU quite a bit
  • Comes in too many pieces, here I mean there are way too many diverse extensions that often belong to different vendors or providers
  • The "schemas" are over-thought
  • Lack of some minor basic DML features as MERGE/UPSERT (however can be done with "On Conflict"), also lacking an ability to reposition table column, case sensitive when it comes to database objects
  • No explicit user control over data compression
  • The administration can be done with fewer people.
  • Ease of hosting, migration, and integration is very good.
  • Ready to use programming interfaces, low overall effort to incorporate.
  • Some negative impact when it comes to use with commercial enterprise reporting tools. Feature-set or behind the scenes query generation could be sub-optimal.
  • Good commercial client tools are highly recommended but would be costly.
PostgreSQL beats every other RDBMS offering for being truly Open Source. Since it does not belong to a specific company it is poised to remain as such for a long time to come. PostgreSQL has a huge user base and active community. The releases are coming out often with substantial improvements and the backward compatibility is first-class. The multi-paradigm programmability model is awesome - almost no limit, most diverse developers can work together, and it has more extensions than any of the RDBMS on the market.
I am split between somewhere 6 and 8 so I gave it a 7 largely because the support is via a user community if you are on the freeware version, which entitles you no guarantee in time or quality of support, but most of the quirks are well described with numerous remedies possible. When PostgreSQL comes from for-profit vendors, say MemSQL or Citus, the support situation goes multiple notches up because they want to ensure your success. In AWS as RDS the support it a tad anemic, but works.

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PostgreSQL is a go-to database for any web application, especially if one is going to reside with one of the many hosting/Cloud providers. It can analyze some, up to a few TBs, of transactional data, or can be used in data warehouses, and extending it - Geospatial, JSON, Failover, Replication are all within reach.

Not so great for ETL or large volume data processing, e.g. pulling data from foreign sources is not easy often. It is slow to read so any large table scans would be detrimental speed-wise or noticeable to end-users. No in-memory storage, so not good as cache.