DBMS > BaseX vs. Google BigQuery vs. InfluxDB vs. Oracle

System Properties Comparison BaseX vs. Google BigQuery vs. InfluxDB vs. Oracle

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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

DBMS for storing time series, events and metrics

Widely used RDBMS

Primary database model

Secondary database models

Spatial DBMS

with GEO package

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

basex.org

cloud.google.com/bigquery

www.influxdata.com/products/influxdb-overview

www.oracle.com/database

Technical documentation

docs.basex.org

cloud.google.com/bigquery/docs

docs.influxdata.com/influxdb

docs.oracle.com/en/database

Developer

BaseX GmbH

Google

Oracle

Initial release

2007

2010

2013

1980

Current release

11.0, June 2024

2.7.6, April 2024

23c, September 2023

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

MIT-License; commercial enterprise version available

commercial

restricted free version is available

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

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

XQuery supports types

yes

Numeric data and Strings

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

SQL

Support of SQL

yes

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

RESTful HTTP/JSON API

HTTP API
JSON over UDP

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

PL/SQL

also stored procedures in Java possible

Triggers

yes

via events

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

multiple readers, single writer

Since BigQuery is designed for querying data

ACID

isolation level can be parameterized

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

Depending on used storage engine

yes

Version 12c introduced the new option 'Oracle Database In-Memory'

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)

simple rights management via user accounts

fine grained access rights according to SQL-standard

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