DBMS > Derby vs. Postgres-XL vs. Qdrant vs. Snowflake

System Properties Comparison Derby vs. Postgres-XL vs. Qdrant vs. Snowflake

Please select another system to include it in the comparison.

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.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Vector DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.28
Rank	#167	Overall
	#6	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

db.apache.org/derby

www.postgres-xl.org

github.com/qdrant/qdrant
qdrant.tech

www.snowflake.com

Technical documentation

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

www.postgres-xl.org/documentation

qdrant.tech/documentation

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Qdrant

Snowflake Computing Inc.

Initial release

1997

2014

since 2012, originally named StormDB

2021

2014

Current release

10.17.1.0, November 2023

10 R1, October 2018

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

Mozilla public license

Open Source

Apache Version 2.0

commercial

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

Rust

Server operating systems

All OS with a Java VM

Linux
macOS

Docker
Linux
macOS
Windows

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

XML type, but no XML query functionality

yes

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC

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

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

CLI Client
JDBC
ODBC

Supported programming languages

Java

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Collection-level replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency, tunable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

MVCC

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

fine grained access rights according to SQL-standard

Key-based authentication

Users with fine-grained authorization concept, user roles and pluggable 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.