DBMS > BaseX vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. MongoDB vs. Oracle Berkeley DB

System Properties Comparison BaseX vs. Google Cloud Spanner vs. Microsoft Azure Data Explorer vs. MongoDB vs. Oracle Berkeley DB

Editorial information provided by DB-Engines

Name

Description

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

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Fully managed big data interactive analytics platform

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

Widely used in-process key-value store

Primary database model

column oriented

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	2.84
Rank	#100	Overall
	#51	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	2.01
Rank	#126	Overall
	#21	Key-value stores
	#3	Native XML DBMS

Website

basex.org

cloud.google.com/spanner

azure.microsoft.com/services/data-explorer

www.mongodb.com

www.oracle.com/database/technologies/related/berkeleydb.html

Technical documentation

docs.basex.org

cloud.google.com/spanner/docs

docs.microsoft.com/en-us/azure/data-explorer

www.mongodb.com/docs/manual

docs.oracle.com/cd/E17076_05/html/index.html

Developer

BaseX GmbH

Google

Microsoft

MongoDB, Inc

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2007

2017

2019

2009

1994

Current release

11.0, June 2024

cloud service with continuous releases

6.0.7, June 2023

18.1.40, May 2020

License

Commercial or Open Source

Open Source

BSD license

commercial

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

commercial license available

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

MongoDB Flex @ STACKIT offers managed MongoDB Instances with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.

Implementation language

Java

C++

C, Java, C++ (depending on the Berkeley DB edition)

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Solaris
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

schema-free

Typing

predefined data types such as float or date

XQuery supports types

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

only with the Berkeley DB XML edition

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

Kusto Query Language (KQL), SQL subset

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

Go
Java
JavaScript (Node.js)
Python

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

JavaScript

Triggers

yes

via events

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

in MongoDB Atlas only

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication with 3 replicas for regional instances.

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Spark connector (open source): github.com/Azure/azure-kusto-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

multiple readers, single writer

ACID

Strict serializable isolation

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

In-memory storage engine introduced with MongoDB version 3.2

yes

User concepts

Access control

Users with fine-grained authorization concept on 4 levels

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Azure Active Directory Authentication

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
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Market metrics

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Licensing and pricing models

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