DBMS > PostgreSQL vs. RavenDB vs. StarRocks vs. XTDB

System Properties Comparison PostgreSQL vs. RavenDB vs. StarRocks vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Widely used open source RDBMS

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

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

Document store

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	2.59
Rank	#95	Overall
	#17	Document stores

Score	0.94
Rank	#188	Overall
	#86	Relational DBMS

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

www.postgresql.org

ravendb.net

www.starrocks.io

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.postgresql.org/docs

ravendb.net/docs

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

www.xtdb.com/docs

Developer

PostgreSQL Global Development Group

www.postgresql.org/developer

Hibernating Rhinos

The Linux Foundation

since Feb 2023

Juxt Ltd.

Initial release

1989

1989: Postgres, 1996: PostgreSQL

2010

2020

2019

Current release

16.4, August 2024

5.4, July 2022

3.3, June 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

BSD

Open Source

AGPL version 3, commercial license available

Open Source

Apache Version 2.0

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java

Clojure

Server operating systems

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

Linux
macOS
Raspberry Pi
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language (RQL)

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

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

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
MySQL protocol

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

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

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning (by range and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

Role based access control and fine grained access rights

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