DBMS > Ignite vs. Qdrant vs. Stardog

System Properties Comparison Ignite vs. Qdrant vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

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

Primary database model

Key-value store
Relational DBMS

Vector DBMS

Graph DBMS
RDF store

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

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

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

Website

ignite.apache.org

github.com/qdrant/qdrant
qdrant.tech

www.stardog.com

Technical documentation

apacheignite.readme.io/docs

qdrant.tech/documentation

docs.stardog.com

Developer

Apache Software Foundation

Qdrant

Stardog-Union

Initial release

2015

2021

2010

Current release

Apache Ignite 2.6

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2.0

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

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++, Java, .Net

Rust

Java

Server operating systems

Linux
OS X
Solaris
Windows

Docker
Linux
macOS
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

Numbers, Strings, Geo, 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

Keywords, numberic ranges, geo, full-text

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, 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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

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

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

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

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)

Collection-level replication

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

Eventual Consistency, tunable 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

Key-based authentication

Access rights for users and roles

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More resources

Recent citations in the news

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Real-time in-memory OLTP and Analytics with Apache Ignite on AWS | Amazon Web Services
14 May 2016, AWS Blog

provided by Google News

Open source vector database startup Qdrant raises $28M
23 January 2024, TechCrunch

Qdrant offers managed vector database for hybrid clouds
16 April 2024, InfoWorld

Qdrant Hybrid Cloud is Now Available for OCI Customers: Managed Vector Search Engine for Data-Sensitive AI ...
16 April 2024, Oracle

Open-source vector database Qdrant launches hybrid cloud for enterprise AI apps
16 April 2024, SiliconANGLE News

Qdrant launches first vector database as a managed hybrid cloud
16 April 2024, VentureBeat

provided by Google News

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