DBMS > Derby vs. H2 vs. Qdrant vs. TigerGraph

System Properties Comparison Derby vs. H2 vs. Qdrant vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Relational DBMS

Vector DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

db.apache.org/derby

www.h2database.com

github.com/qdrant/qdrant
qdrant.tech

www.tigergraph.com

Technical documentation

db.apache.org/derby/manuals/index.html

www.h2database.com/html/main.html

qdrant.tech/documentation

docs.tigergraph.com

Developer

Apache Software Foundation

Thomas Mueller

Qdrant

Initial release

1997

2005

2021

2017

Current release

10.17.1.0, November 2023

2.2.220, July 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2.0

commercial

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

Java

Rust

C++

Server operating systems

All OS with a Java VM

Docker
Linux
macOS
Windows

Linux

Data scheme

yes

schema-free

yes

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

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC

JDBC
ODBC

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Java

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

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Key-based authentication

Role-based access control

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