DBMS > GridGain vs. PostgreSQL vs. Qdrant

System Properties Comparison GridGain vs. PostgreSQL vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

Widely used open source RDBMS

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

A high-performance vector database with neural network or semantic-based matching

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Relational DBMS

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

Vector 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	1.32
Rank	#151	Overall
	#1	Columnar
	#25	Key-value stores
	#2	Object oriented DBMS
	#68	Relational DBMS

Score	667.25
Rank	#4	Overall
	#4	Relational DBMS

Score	2.23
Rank	#106	Overall
	#8	Vector DBMS

Website

www.gridgain.com

www.postgresql.org

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

www.gridgain.com/docs/index.html

www.postgresql.org/docs

qdrant.tech/documentation

Developer

GridGain Systems, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Qdrant

Initial release

2007

1989

1989: Postgres, 1996: PostgreSQL

2021

Current release

GridGain 8.5.1

16.4, August 2024

License

Commercial or Open Source

commercial, open source

Open Source

BSD

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

PostgreSQL Flex @ STACKIT offers managed PostgreSQL Instances with adjustable CPU, RAM, storage amount and speed and several extensions available, in enterprise grade to perfectly match all application requirements. All 100% GDPR-compliant.

Implementation language

Java, C++, .Net, Python, REST, SQL

Rust

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

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

Docker
Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, Boolean

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

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

standard with numerous extensions

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

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

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

other methods possible by using 3rd party extensions

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable 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

Role-based access control
Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Key-based authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.