DBMS > Faircom DB vs. HyperSQL vs. JanusGraph vs. Qdrant

System Properties Comparison Faircom DB vs. HyperSQL vs. JanusGraph vs. Qdrant

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

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

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Graph DBMS

Vector DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	1.85
Rank	#134	Overall
	#12	Graph DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Website

www.faircom.com/products/faircom-db

hsqldb.org

janusgraph.org

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

hsqldb.org/web/hsqlDocsFrame.html

docs.janusgraph.org

qdrant.tech/documentation

Developer

FairCom Corporation

Linux Foundation; originally developed as Titan by Aurelius

Qdrant

Initial release

1979

2001

2017

2021

Current release

V13, July 2024

2.7.2, June 2023

1.0.0, October 2023

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

based on BSD license

Open Source

Apache 2.0

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.

Implementation language

ANSI C, C++

Java

Rust

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

All OS with a Java VM

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

Linux
OS X
Unix
Windows

Docker
Linux
macOS
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

yes

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

All languages supporting JDBC/ODBC
Java

Clojure
Java
Python

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

none

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

none

yes

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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 with additional protections for files

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FairCom Unveils New Look, FairCom DB v13: Introducing 'DB Made Simple'
4 June 2024, Business Wire

provided by Google News

HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

provided by Google News

Simple Deployment of a Graph Database: JanusGraph
12 October 2020, Towards Data Science

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

Compose for JanusGraph arrives on Bluemix
15 September 2017, ibm.com

provided by Google News

Qdrant review: A highly flexible option for vector search
29 July 2024, InfoWorld

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

Vector database company Qdrant wants RAG to be more cost-effective
2 July 2024, VentureBeat

Qdrant Announces an Industry-First Hybrid Cloud Offering For Enterprise AI Applications
16 April 2024, Business Wire

Qdrant unveils hybrid vector algorithm for improved RAG
2 July 2024, Blocks & Files

provided by Google News

Share this page