DBMS > GridGain vs. HyperSQL vs. Pinecone vs. Stardog

System Properties Comparison GridGain vs. HyperSQL vs. Pinecone vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

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

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A managed, cloud-native vector database

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Vector DBMS

Graph DBMS
RDF store

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	3.16
Rank	#95	Overall
	#2	Vector DBMS

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

www.gridgain.com/docs/index.html

hsqldb.org/web/hsqlDocsFrame.html

docs.pinecone.io/docs/overview

docs.stardog.com

Developer

GridGain Systems, Inc.

Pinecone Systems, Inc

Stardog-Union

Initial release

2007

2001

2019

2010

Current release

GridGain 8.5.1

2.7.2, June 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, C++, .Net

Java

Server operating systems

Linux
OS X
Solaris
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

String, Number, Boolean

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

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

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

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

HTTP API

JDBC via HTTP
JDBC
ODBC

RESTful HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC
Java

Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

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

Java, SQL

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes (cache interceptors and events)

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

none

Multi-source replication in HA-Cluster

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

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

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Recent citations in the news

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & Files

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