DBMS > Apache Pinot vs. LeanXcale vs. PostgreSQL vs. Valentina Server

System Properties Comparison Apache Pinot vs. LeanXcale vs. PostgreSQL vs. Valentina Server

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Widely used open source RDBMS

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

Object-relational database and reports server

Primary database model

Relational DBMS

Key-value store
Relational DBMS

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

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

Score	0.35
Rank	#274	Overall
	#128	Relational DBMS

Score	0.28
Rank	#286	Overall
	#41	Key-value stores
	#130	Relational DBMS

Score	644.36
Rank	#4	Overall
	#4	Relational DBMS

Score	0.18
Rank	#313	Overall
	#140	Relational DBMS

Website

Technical documentation

docs.pinot.apache.org

www.postgresql.org/docs

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Apache Software Foundation and contributors

LeanXcale

PostgreSQL Global Development Group

www.postgresql.org/developer

Paradigma Software

Initial release

2015

1989

1989: Postgres, 1996: PostgreSQL

1999

Current release

1.0.0, September 2023

16.4, August 2024

5.7.5

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

All OS with a Java JDK11 or higher

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

Linux
OS X
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

yes

through Apache Derby

yes

standard with numerous extensions

yes

APIs and other access methods

JDBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

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

ODBC

Supported programming languages

Go
Java
Python

C
Java
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

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More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2022, defending the title from last year
3 January 2023, Matthias Gelbmann, Paul Andlinger

Snowflake is the DBMS of the Year 2021
3 January 2022, Paul Andlinger, Matthias Gelbmann

show all

Conferences, events and webinars

more DBMS events

PASS Data Community Summit
Seattle, Washington, 4-8 November 2024

Recent citations in the news

Pinot for Low-Latency Offline Table Analytics
29 August 2024, Uber

Build a real-time analytics solution with Apache Pinot on AWS
6 August 2024, AWS Blog

Open source Apache Pinot advances as StarTree boosts real-time analytics and observability
8 May 2024, VentureBeat

StarTree broadly enhances Apache Pinot-based analytics platform
8 May 2024, SiliconANGLE News

StarTree Finds Apache Pinot the Right Vintage for IT Observability
8 May 2024, Datanami

provided by Google News

YugabyteDB 2.19 gets new PostgreSQL-compatibility features
19 September 2024, InfoWorld

YugabyteDB evolves into a distributed PostgreSQL database for apps that need resilience and scale
19 September 2024, SiliconANGLE News

Intel Demonstrates Up To 48% Improvement For AVX-512 Optimized PostgreSQL
12 September 2024, Phoronix

PostgreSQL in line for DuckDB-shaped boost in analytics arena
20 August 2024, The Register

PostgreSQL databases under attack
21 August 2024, Help Net Security

provided by Google News

A Look at Valentina
18 April 2014, SitePoint

MySQL GUI Tools for Windows and Ubuntu/Linux: Top 8 free or open source
7 December 2018, H2S Media

provided by Google News

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