DBMS > BaseX vs. Google BigQuery vs. Qdrant vs. Warp 10

System Properties Comparison BaseX vs. Google BigQuery vs. Qdrant vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Light-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.

Large scale data warehouse service with append-only tables

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	1.53
Rank	#145	Overall
	#7	Vector DBMS

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

basex.org

cloud.google.com/bigquery

github.com/qdrant/qdrant
qdrant.tech

www.warp10.io

Technical documentation

docs.basex.org

cloud.google.com/bigquery/docs

qdrant.tech/documentation

www.warp10.io/content/02_Getting_started

Developer

BaseX GmbH

Google

Qdrant

SenX

Initial release

2007

2010

2021

2015

Current release

11.2, August 2024

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

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

Java

Server operating systems

Linux
OS X
Windows

hosted

Docker
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

XQuery supports types

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.

Secondary indexes

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

yes

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

HTTP API
Jupyter
WebSocket

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

WarpScript

Triggers

yes

via events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

Collection-level replication

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

multiple readers, single writer

Since BigQuery is designed for querying data

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

Users with fine-grained authorization concept on 4 levels

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Key-based authentication

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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