DBMS > KeyDB vs. PostgreSQL vs. Trino

System Properties Comparison KeyDB vs. PostgreSQL vs. Trino

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Editorial information provided by DB-Engines

Name

Description

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

Primary database model

Key-value store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Relational DBMS

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.67
Rank	#226	Overall
	#31	Key-value stores

Score	663.41
Rank	#4	Overall
	#4	Relational DBMS

Score	5.40
Rank	#61	Overall
	#35	Relational DBMS

Website

github.com/Snapchat/KeyDB
keydb.dev

www.postgresql.org

trino.io

Technical documentation

docs.keydb.dev

www.postgresql.org/docs

trino.io/broadcast
trino.io/docs/current

Developer

EQ Alpha Technology Ltd.

PostgreSQL Global Development Group

www.postgresql.org/developer

Trino Software Foundation

Initial release

2019

1989

1989: Postgres, 1996: PostgreSQL

2012

2020 rebranded from PrestoSQL

Current release

16.4, August 2024

License

Commercial or Open Source

Open Source

BSD-3

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C++

Java

Server operating systems

Linux

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux
macOS

for devlopment

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

by using the Redis Search module

yes

depending on connected data-source

SQL

Support of SQL

yes

standard with numerous extensions

yes

APIs and other access methods

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
RESTful HTTP API
Trino CLI

Supported programming languages

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

Lua

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes, depending on connected data-source

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

depending on connected data-source

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

depending on connected data-source

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Optimistic locking, atomic execution of commands blocks and scripts

ACID

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

depending on connected data-source

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

simple password-based access control and ACL

fine grained access rights according to SQL-standard

SQL standard access control

More information provided by the system vendor

News

Trino in 2024 and beyond
7 January 2025

Trino Summit 2024 resources
18 December 2024

The long journey to Apache Ranger
2 December 2024

The glorious lineup for Trino Summit 2024
22 November 2024

View the SQL basecamps before Trino Summit
21 November 2024

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