DBMS > BaseX vs. Dragonfly vs. Microsoft Azure Data Explorer vs. MongoDB vs. Teradata

System Properties Comparison BaseX vs. Dragonfly vs. Microsoft Azure Data Explorer vs. MongoDB vs. Teradata

Editorial information provided by DB-Engines

Name

Description

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

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

column oriented

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

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	1.84
Rank	#135	Overall
	#4	Native XML DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	44.87
Rank	#22	Overall
	#15	Relational DBMS

Website

basex.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

azure.microsoft.com/services/data-explorer

www.mongodb.com

www.teradata.com

Technical documentation

docs.basex.org

www.dragonflydb.io/docs

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

www.mongodb.com/docs/manual

docs.teradata.com

Developer

BaseX GmbH

DragonflyDB team and community contributors

Microsoft

MongoDB, Inc

Teradata

Initial release

2007

2023

2019

2009

1984

Current release

11.0, June 2024

1.0, March 2023

cloud service with continuous releases

6.0.7, June 2023

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

BSD license

Open Source

BSL 1.1

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.

commercial

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.

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

hosted

Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

schema-free

scheme-free

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.

yes

Typing

predefined data types such as float or date

XQuery supports types

strings, hashes, lists, sets, sorted sets, bit arrays

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

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

all fields are automatically indexed

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

Read-only SQL queries via the MongoDB Atlas SQL Interface

yes

SQL 2016 + extensions

APIs and other access methods

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

Proprietary protocol

RESP - REdis Serialization Protocol

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

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Actionscript
C
C#
Haskell
Java
JavaScript

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

.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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Lua

Yes, possible languages: KQL, Python, R

JavaScript

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via events

publish/subscribe channels provide some trigger functionality

yes

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

yes

in MongoDB Atlas only

yes

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.

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Transaction concepts

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

multiple readers, single writer

Atomic execution of command blocks and scripts

Multi-document ACID Transactions with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

Azure Active Directory Authentication

Access rights for users and roles

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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Competitive advantages

Built around the flexible document data model and unified API, MongoDB is a developer...
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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

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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