DBMS > Apache Pinot vs. BigchainDB vs. GBase vs. JaguarDB vs. PostgreSQL

System Properties Comparison Apache Pinot vs. BigchainDB vs. GBase vs. JaguarDB vs. PostgreSQL

Editorial information provided by DB-Engines

Name

Description

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

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Performant, highly scalable DBMS for AI and IoT applications

Widely used open source RDBMS

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

Primary database model

Relational DBMS

Document store

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

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

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	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#13	Vector DBMS

Score	636.25
Rank	#4	Overall
	#4	Relational DBMS

Website

Technical documentation

docs.pinot.apache.org

bigchaindb.readthedocs.io/en/latest

www.jaguardb.com/support.html

www.postgresql.org/docs

Developer

Apache Software Foundation and contributors

General Data Technology Co., Ltd.

DataJaguar, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2015

2016

2004

2015

1989

1989: Postgres, 1996: PostgreSQL

Current release

1.0.0, September 2023

GBase 8a, GBase 8s, GBase 8c

3.3 July 2023

16.3, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL v3

commercial

Open Source

GPL V3.0

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java

Python

C, Java, Python

C++

the server part. Clients available in other languages

Server operating systems

All OS with a Java JDK11 or higher

Linux

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

Data scheme

yes

schema-free

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

Standard with numerous extensions

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

standard with numerous extensions

APIs and other access methods

JDBC

CLI Client
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC

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

Supported programming languages

Go
Java
Python

Go
Haskell
Java
JavaScript
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication

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

Eventual Consistency

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,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

User concepts

Access control

yes

rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

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